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October 26, 2007: Video search makes phone a 'second pair of eyes'. By Will Knight. NewScientist.com news. "Soon, however, it may be easier to simply record a video clip of an item of interest and have your phone tell you about it instead. Researchers at Accenture Technology Labs in France have developed technology that makes this possible using any ordinary 3G cellphone equipped with a video camera. ... If a user records a video clip of, say, a foreign food item, the system can automatically identify ingredients that might cause an allergic reaction. Similarly, when shown a book, it can quickly perform an online price comparison, or find a review (see video...). Live video footage is fed from the handset to a central server, which rapidly matches on-screen objects to images previously entered into a database. The server then sends find relevant information and sends it back to user. The central server uses an algorithm called the Scale-Invariant Feature Transform (SIFT) to match objects. ... Microsoft has a system called Lincoln, that lets users to take snapshots and send them off for identification. Another system developed by Evolution Robotics of Pasadena, California, called ViPR, also uses video footage to identify objects, and is already available in Japan."
>>> Image Understanding, Information Retrieval, Machine Learning, Vision, Applications October 25, 2007: Rating Facial Expressions - New software could help mental-health professionals assess patients and ensure that salespeople project a positive attitude. By Anna Davison. Technology Review. "Software that recognizes and rates smiles was demonstrated recently at an exhibition in Tokyo, where attendees competed to outsmile one another. The smile-checking technology is the latest addition to Omron Corporation's OKAO Vision software suite, which detects faces in images and can determine the person's gender and approximate age, or verify his or her identity from a database of faces. The smile software is Omron's first foray into facial-expression detection and analysis, a field that could revolutionize how humans interact with machines, and with each other. ... 'Clearly, it's an interesting thing,' says Joseph Atick of L-1 Identity Solutions, based in Stamford, CT, which supplies identification technology, primarily for security applications. 'If you can read people better, you can serve them better.' ... Sophisticated facial-expression analysis could help mental-health professionals evaluate their patients and monitor their progress." October 22, 2007: 'Smart' video offers an alert to threats - Taking boredom factor out of security systems. By Hiawatha Bray. The Boston Globe. "In video surveillance systems, the weakest link is the often bored, distracted human who has to spend hours staring at a bank of video monitors, waiting for something suspicious to happen. Several Boston area companies say they have found a solution: surveillance systems smart enough to recognize threats, even when their human operators do not. 'It essentially replaces the need for people to watch video,' said Scott Schnell, chief executive of VideoIQ Inc., a Bedford firm that was spun off earlier this year from General Electric Co. ... Systems from VideoIQ and Intuvision Inc. of Woburn can automatically spot an intruder climbing a fence or a subway passenger leaving a suspicious parcel on the platform. ... [Simon] Harris said that worldwide sales of smart video surveillance systems will be less than $100 million this year, but rise to about $3 billion by 2010. ... One test video shows ducks and boats on the Hudson River. The system draws yellow boxes around the harmless ducks, but when a boat appears, the box turns bright red. ... Intuvision, a startup funded by grants from the US intelligence community, has attacked the problem using a technique called 'task-based attention.'"
>>> Law Enforcement, Image Understanding, Vision, Machine Learning, Applications, Industry Statistics October 12, 2007: Surveillance system tracks faces on CCTV - Engineers at UK defence company say hi-tech system will help track suspected terrorists. By Bobbie Johnson. Guardian Unlimited. "Engineers at British defence company BAE Systems, which is working on the technology, claim it is even able to automatically follow a target even if they change their appearance by changing their clothes or hiding beneath a hat. 'Today the effectiveness of CCTV surveillance relies on a small, highly-trained team to identify and track suspicious individuals,' said Andrew Cooke, project manager at BAE Systems. 'Automating elements of the system -- and employing techniques to prevent suspects from throwing a team off their scent -- enables a single operative to track multiple targets with as much, or even greater, precision than before.' The Integrated Surveillance of Crowded Areas for Public Security (Iscaps) project is part of a joint initiative with around Europe to develop security systems for potential deployment around the continent." October 5, 2007: Technology Would Help Detect Terrorists Before They Strike. Press release from the University at Buffalo. " Computer and behavioral scientists at the University at Buffalo are developing automated systems that track faces, voices, bodies and other biometrics against scientifically tested behavioral indicators to provide a numerical score of the likelihood that an individual may be about to commit a terrorist act. 'The goal is to identify the perpetrator in a security setting before he or she has the chance to carry out the attack,' said Venu Govindaraju, Ph.D., professor of computer science and engineering in the UB School of Engineering and Applied Sciences. ... 'We are developing a prototype that examines a video in a number of different security settings, automatically producing a single, integrated score of malfeasance likelihood,' he said. A key advantage of the UB system is that it will incorporate machine learning capabilities, which will allow it to 'learn' from its subjects during the course of a 20-minute interview. That's critical, Govindaraju said, because behavioral science research has repeatedly demonstrated that many behavioral clues to deceit are person-specific." October 4, 2007: Scavenger Champion - Curious George Showcases UBC Advances in Robotic Vision. By Lorraine Chan. UBC Reports. "Jim Little looks forward to the day when robots can make more decisions on their own. Little specializes in the integration of robotics and vision systems. As the Director of UBC’s Laboratory of Computational Intelligence (LCI), Little seeks to penetrate the mysteries of machine vision, comprehension and action. ... Showing prowess in all these areas is Curious George, LCI’s robot which walked away -- or in this case rolled away -- with first prize at an international competition this July. The “Semantic Robot Vision Challenge” tested the mettle of each robot through a three-hour scavenger hunt. The competition was held in Vancouver at the Association for the Advancement of Artificial Intelligence conference and was sponsored by the U.S. National Foundation for Science. ... Little says UBC’s past advances in robotic vision helped Curious George ace this challenge. During the early 1990s, Little invented stereo-vision mapping to enhance computer vision. ... The LCI team wrote software for Curious George to Google the Internet, generating hundreds of relevant images for each scavenger hunt item. Using this database of images, the robot was then well poised to locate the three-dimensional object as it scooted around the room. Little says he hopes to apply LCI advances to creating assistive technologies. Such devices would include wheelchairs that can navigate obstacles, or a smart house that reminds you to turn off the stove. 'These robot-human interactions will enable older people to stay in their homes and live independently as long as possible.' ... To accelerate Canada’s advances in these types of projects, Little says researchers have established a national network called ICAST (Intelligent Computational Assistive Technologies)."
>>> Vision, Robots, Assistive Technologies, Smart Houses, Competitions -and- AI Academic Departments (@ Resources for Students), Applications September 28, 2007: Artificial brain falls for optical illusions - AI software that misjudges colour in the same way as humans suggests that robots must inherit our flaws if they are to have our strengths. By David Robson. NewScientist.com news. "A computer program that emulates the human brain falls for the same optical illusions humans do. It suggests the illusions are a by-product of the way babies learn to filter their complex surroundings. ... For some time, scientists have believed one class of optical illusions result from the way the brain tries to disentangle the colour of an object and the way it is lit. ... Until now there has been no way of knowing whether this theory is correct. Beau Lotto and David Corney at University College London, UK, think they have finally done it. They created a program that learns to predict the lightness of an image based on its past experiences -- just like a baby. And just like a human, it falls prey to optical illusions. ... Most creators of machine vision try to copy human vision because it is so well suited to a variety of environments. The new findings suggest that if we want to exploit its advantages, we also have to suffer its failings." September 21, 2007: Smile - you're on camera! Face recognition is only the beginning. Web only Tech.view column. Economist.com. "Now face-recognition technology is getting even smarter. Next week, Sony is due to launch a digital camera that can be set so it won’t release the shutter until people in the picture are smiling. ... If the face-recognition problem can be truly solved (ie, if an identity can be attached to a person in an image, irrespective of lighting, orientation, occlusion, pose, expression or adornment), then we will be well on the way to licking one of the greatest challenges in artificial intelligence -- computerised vision. The pay off for cancer screening, road safety, security, computer interfaces, video compression and, of course, digital cameras could be immense." September 12, 2007: Software turns photos from bad to good - Program searches Flickr to make imperfect photos into great pictures. By Bryn Nelson. MSNBC.com. "With some help from the Flickr photo-sharing Web site, two researchers at Pittsburgh’s Carnegie Mellon University have shown how a new picture-patching program can transform flawed vacation shots into 'Wow!'-worthy masterpieces. ... Unlike existing programs that use bits of the same photo to patch holes, the new program relies on an algorithm that first searches through heaps of digital photos -- 2.3 million downloaded from Flickr in this case -- for ones that match the gist of the scene. ... The program then looks within that subset for good patches by blending candidates with the target photo and finding boundaries that would be least noticeable to viewers. ... [Professor Alexei] Efros said getting a computer to produce a composite scene that is not only seamless but also contextually valid reflects a main challenge of artificial intelligence research."
>>> Vision, Image Understanding, Applications September 7, 2007: Spanish researchers develop award-winning ancient manuscript recognition system. CORDIS News. "The scientists, from the Autonomous University of Barcelona's Computer Vision Centre, have designed the efficient Blurred Shape Model (BSM) to be able to work with ancient, damaged or difficult to read manuscripts, handwritten scores and architectural drawings. According to the scientists, their research represents an effective human machine interface able to automatically reproduce documents while they are being written or drawn. The researchers won the first prize in the third edition of the Iberian Conference on Pattern Recognition and Image Analysis (IbPRIA) for their model." September 6, 2007: Science fiction becoming science fact - Venu Govindaraju spearheads cutting-edge research at CUBS, CEDAR. By Kevin Fryling. UB Reporter. "In the future, UB faculty member Venu Govindaraju says, cameras will recognize passengers' faces at the airport, ... These are but a few applications of the cutting-edge research that Govindaraju spearheads as founding director of UB's Center for Unified Biometrics and Sensors (CUBS) and associate director of the Center for Document Analysis and Recognition (CEDAR). ... About half of Govindaraju's research relates to the field of biometrics, which he describes as 'the science of identifying people.' His introduction to the subject, he notes, came from his thesis work on facial recognition -- a subject once considered more relevant to artificial intelligence than biometrics -- and since then he has been at the forefront of biometrics' transformation into a red-hot field in computer science due to rising interest in both personal and national security. ... Nowadays, Govindaraju says, CUBS looks at different aspects of biometrics. 'We look at facial recognition, voice recognition, fingerprint recognition' -- as well as iris recognition, gait recognition, odor detection and hand geometry -- 'and how to combine these different methods.' ... Govindaraju also points to his efforts to create algorithms that comprehend handwritten text in Arabic, English, Hindi and Sanskrit-he is fluent in the latter three languages -- as a further source of collaboration with UB colleagues. August 31, 2007: 'Smart' Traffic Signals Save Dumb Drivers. By Tracy Staedter. Discovery Channel News. "The smart signal, in development at the Technion-Israel Institute of Technology, is part of a bigger transportation infrastructure being designed to incorporate computers and automated systems to improve traffic flow and safety. Such a system could work to not only alert individual drivers, but also to prevent accidents and track violations. The alert system consists of two standard surveillance cameras, each mounted on a pole at an intersection. ... Image processing software discerns moving cars from the background and determines how fast the vehicles are traveling. The software automatically projects the cars' trajectories and, based on their speed and direction, calculates the likelihood of a collision."
>>> Transportation, Vision, Applications August 21, 2007: Machine vision aids animal management. By Jennifer Foreshew. Australian IT. "Australian researchers have developed a computerised system that uses Machine Vision Technology to help farmers manage domestic and wild animals on their properties. The system is capable of distinguishing between sheep, goats, cattle, horses, pigs, kangaroos and emus and can be used with other species. Machine vision is the ability of a computer to see. It uses cameras, analogue-to-digital conversion and digital signal processing. The data goes to a computer or robot controller. The project involves the University of Queensland, the University of Southern Queensland the federal government and RPM Rural Products. ... The system identifies animals and controls their movements via automated gates to access watering or feed points. It is expected to boost farmers' productivity and efficiency in remote areas and control loss of feed and water to feral animals."
>>> Agriculture, Natural Resource Management, and the Environment, Vision, Applications August 18, 2007 [issue date]: Robots surf the web to learn about the world. By Michael Reilly. New Scientist (Issue 2617: pages 22 - 23; subscription req'd). "Just as you might run a Google image search to see what a Buddha's hand citron looks like, so robots, and computer programs, are starting to take advantage of the wealth of images posted online to find out about everyday objects. When presented with a new word, instead of using the limited index it has been programmed with, which is the conventional method, this new breed of automatons goes online and enters the word into Google. The robot or software uses the resulting range of images to recognise the object in the real world. ... To test the idea, last month [Paul] Rybski, together with colleague Alexei Efros, organised the first Semantic Robot Vision Challenge at the annual conference of the American Association for Artificial Intelligence in Vancouver. Four teams took part, entering one robot each. The robots were given a list of 20 objects, including a DVD, a CD case, a banana and a calculator, that would be strewn across tables and chairs in a 6-metre-square area. The robots were allowed one hour to search the internet for images that were relevant to the words on the list and to analyse them. After that, they had to set out in search of the items. ... Curious George ended up winning, by identifying seven of the 20 objects, including distinguishing between a red bell pepper and a red plastic cup, which had been deliberately added to cause confusion." August 16, 2007: How Do Post Office Machines Read Addresses? By Ben Mauk. LiveScience.com. "The United States Postal Service (USPS) began researching remote computer readers (RCRs) for handwritten addresses in 1983. At the time, the technology required to scan and understand a human scrawl simply did not exist. Not until Christmas of 1997 did the USPS and the University of Buffalo's Center for Excellence in Document Analysis and Recognition (CEDAR) deploy its first handwritten address-reading prototype.... Humans read and comprehend with an ease that belies the immense difficulty of computer pattern recognition (including patterns such as numbers and letters). It is one of the central problems in artificial intelligence. ... 'That Christmas alone we saved several thousand dollars for the post office,' Sargur Srihari told LiveScience. Srihari founded CEDAR and led the early research on large-scale RCRs. Today, the large majority of letters sent through the post office are read and sorted entirely by computer. According to Srihari, current reading success rates are above 90 percent." August 13, 2007: On track. The Engineer Online. "A technology being used to identify possible criminals or terrorists in a crowd may help UK in its bid for medals at the 2012 Olympics. The analysis of body movement using artificial intelligence helps security services pick out unusual body movements and suspicious behaviour at events such as rallies or football matches. Now, Muscle Memory Second Generation (MM2G) is developing a web-based product that will use the same technology to enhance the sports performance of professional and amateur athletes. ... 'The aim is to marry artificial intelligence and behavioural templates to sports science and performance. The resulting product will take sports training and performance analysis onto the internet,' said [Winslie] Gomez. 'We are going to be taking on a postgraduate student who will create the normalised templates of how the body behaves during sports, using artificial intelligence.'" August 12, 2007: China Enacting a High-Tech Plan to Track People. By Keith Bradsher. The New York Times. "At least 20,000 police surveillance cameras are being installed along streets here in southern China and will soon be guided by sophisticated computer software from an American-financed company to recognize automatically the faces of police suspects and detect unusual activity. ... [R]ising fears of terrorism have lessened public hostility to surveillance cameras in the West. This has been particularly true in Britain, where the police already install the cameras widely on lamp poles and in subway stations and are developing face recognition software as well. New York police announced last month that they would install more than 100 security cameras to monitor license plates in Lower Manhattan by the end of the year. Police officials also said they hoped to obtain financing to establish links to 3,000 public and private cameras in the area by the end of next year; no decision has been made on whether face recognition technology has become reliable enough to use without the risk of false arrests. ... Some civil rights activists contend that the cameras in China and Britain are a violation of the right of privacy contained in the International Covenant on Civil and Political Rights." August 7, 2007: Keeping Drunks off the Road - Nissan unveils new technologies that can identify drunk or drowsy drivers. By John Borland. Technology Review. "The latest and most ambitious of these in-car sobriety checks comes from Nissan, which unveiled a new demonstration car late last week in Japan. The demonstration offers a full suite of monitoring systems, ranging from cameras that recognize drooping eyelids to stick-shift sensors that measure alcohol content in sweat. All systems are aimed at automatically determining whether a driver is safe for the road. ... [A] camera mounted on the steering wheel monitors the driver's face, looking for signs that he or she is dozing off. This system, developed by Nissan in conjunction with unidentified partners, uses facial-recognition technology that identifies a broad range of features--eyes, nose, mouth, and so on--before focusing on the eyes. A calibration tool learns an individual's patterns of opening and closing his or her eyes, turning this into what Nissan calls a closed-eye ratio. Because of the wide variation from individual to individual, blinking is excluded from this ratio, [Terry] Steeden says." July 17, 2007: Looking for Signs of Life - New facial-recognition software features a test that can root out fraudsters trying to pass off a photograph as a real person. By Duncan Graham-Rowe. Technology Review. "Scientists in Sweden have developed a liveness-detection system that they say should help reduce the chances of face-biometrics systems being fooled by photographs. 'Liveness is going to be a major issue for biometrics,' says Josef Bigun, a professor of signal analysis who led the research at Halmstad University, in Sweden. This is particularly the case with face recognition. '[Today's systems] cannot tell the difference between a picture and a face,' he says." July 16, 2007: Emotion-Recognition Software Knows What Makes You Smile. By Nicole Martinelli. Wired. "A computer program that reads human expressions may bring an about-face in marketing. ... Marketers increasingly use technology to determine what gives consumers bliss. ... But how does software analyze emotion? ... Emotion-recognition software, or ERS, creates a 3-D face map, pinpointing 12 key trigger areas like eye and mouth corners. Then a face-tracking algorithm matches the movements to six basic expression patterns, corresponding to anger, sadness, fear, surprise, disgust and happiness, or a mixture of them." June 22, 2007: Big Brother is watching you... and he's a computer - The threat of cameras combined with artificial intelligence. By Mike Elgan. Computerworld. "Privacy activists have been lamenting increasing surveillance by cameras and warn of abuse by the authorities who have access to them. But two additional trends portend a disturbing new direction. The first trend: Cameras are increasingly monitoring non-criminals engaged in technically legal behavior. The second trend: Special new artificial intelligence software is processing video feeds to look for unacceptable behavior. The machines are watching us, and they are making judgments about what we do. Another way of looking at these colliding trends is that we are beginning to offload the human capacity for ethics, morality and good citizenship to computer systems. ... The new surveillance technology is impressive, and can help counter major crimes and terrorist acts and save lives. But less impressive are our rules, guidelines and restrictions on the growing use of cameras and artificial intelligence to monitor minor crimes and non-criminal activity." June 11, 2007: A Dog or a Cat? New Tests to Fool Automated Spammers. By Brad Stone. The New York Times. "On the Internet, nobody knows you’re a human -- until you fill out a captcha. Captchas [Completely Automated Public Turing Test to Tell Computers and Humans Apart] are the puzzles on many Web sites that present a string of distorted letters and numbers. These are supposed to be easy for people to read and retype, but hard for computer software to figure out. ... The emergence of the technology started a wave of research into ways to make computers smart enough to crack the puzzles. ... Microsoft researchers have developed an alternative captcha that asks Internet users to view nine images of household pets and then select just the cats or the dogs. 'For software, this is wildly hard,' said John Douceur, a Microsoft researcher. 'Computers are tripped up by all the photos at different angles, with variable lighting conditions and backgrounds and the animals in different positions.' The project, called Asirra (for Animal Species Image Recognition for Restricting Access), uses photographs of animals from Petfinder.com, a site that finds homes for homeless pets and has more than two million images in its database." June 6, 2007: My car is watching me. By Ryan Pearson. The Associated Press / available from The Olympian Online. "While you're watching the road, your future car could be watching you. Researchers and automakers are developing steering wheel- and dashboard-mounted sensors that peer at a driver's face to determine what's going on inside your head. The hope is these electronic spies will - either through brute force or gentle prodding - keep you from crashing. ... By recognizing emotion and context via face-recognition technology, cars can respond in a useful way. For example, if a driver is drowsy, the car may begin an audio program teaching a pre-set language that forces the driver to repeat a word every once in a while. Don't sleep! Learn French instead! Or if someone cuts you off and the car detects anger, it will automatically yell at the jerk for you. 'It's about how you help people manange your emotions in the car,' Nass said. 'It's catharsis. That'll dissipate your anger.' [Stanford professor Clifford Nass] said Toyota in particular has been working on sensing emotion and shifting even the voice of the car based on context - if a driver hit heavy fog the car's voice could get more tentative. The researcher predicts that within five years, such features will be included on consumer-ready cars, at least in Japan." June 2007: Security needs open numerous opportunities - A discussion with Juan Herrera, Perceptics. Vision Systems Design. "Herrera: ... I’m most interested in real-time unconstrained character-recognition applications-what we like to call 'extreme character recognition.' That includes reading license plates for real-time threat assessment, identifying the ISO container code that uniquely identifies every intermodal shipping container, and associating that data with other images and sensor information. In addition to being robust, fast, and accurate, the character-recognition algorithms have to be font independent, and rotation and scale tolerant. ... VSD: What algorithms and specific software developments do you see emerging in the next five years? Herrera: I think new video-compression algorithms will take full advantage of broadband network bandwidth and allow real-time transmission of live video over a network. I see the pairing of machine learning algorithms and image processing as a way of solving somewhat complex inspection tasks. ... VSD: When do you see biologically inspired models of the human visual system and the human cognitive process emerging, and how do you think these will be implemented? ... VSD: Which areas present the most opportunities for engineers involved in machine vision or image processing? Herrera: Ever since 9/11/2001, all applications dealing with security, such as law enforcement, protection, crime prevention, surveillance, and forensic analysis, have incorporated video images into the volume of data that is continuously captured, analyzed, and stored. I think this is a vast field with lots of potentially profitable opportunities." May 30, 2007: Better Face Recognition Software - Computers outperform humans at recognizing faces in recent tests. By Mark Williams. Technology Review. "For scientists and engineers involved with face-recognition technology,the recently released results of the Face Recognition Grand Challenge--more fully, the Face Recognition Vendor Test (FRVT) 2006 and the Iris Challenge Evaluation (ICE) 2006--have been a quiet triumph. Sponsored by the National Institute of Standards and Technology (NIST), the match up of face-recognition algorithms showed that machine recognition of human individuals has improved tenfold since 2002 and a hundredfold since 1995. ... Among other advantages, 3-D facial recognition identifies individuals by exploiting distinctive features of a human face's surface.... How does the commercial payoff for face recognition look? Quite promising, because dozens of companies aim to cash in on face recognition's potential as a biometric for credentialing and verification purposes. ... In principle, therefore, as face-recognition software continues its rapid advance, it will likely be possible to search for specific faces across a network of webcams. Accordingly, [Ralph] Gross's recent work at Carnegie Mellon, in conjunction with colleagues at the Data Privacy Lab there, has been the development of algorithms to protect individuals' privacy while under video surveillance." May 28, 2007 [issue date]: Signs That Can See. By Rupali Arora. Newsweek International / available from MSNBC.com. "Imagine watching an advertisement that is watching you. Sound creepy? Some billboards can already communicate by text or photo message with passersby, and researchers are now endowing these signs with artificial intelligence that can take cues from viewers' behavior. Scientists at National Information and Communications Technology Australia, a government-funded research lab, have developed a billboard technology that watches body language and can tell when you're bored and when you're paying attention. ... This is the future of 'agile retail' technology, one of the fastest-growing areas of advertising. ... One of the advantages of having a camera trained on the potential consumer is that it could give advertisers feedback." May 23, 2007: Compound-Eye Camera Analyzes Scenes. By Kate Greene. Technology Review. "Researchers at the University of Osaka have developed an ultrathin camera that can determine the distance between objects in a scene and pick out color and structural features. ... The basic idea behind the technology is that multiple lenses capture information about a scene from slightly different angles, just as our eyes look at an object from two distinct points of view. ... Essentially, our brains compare the input from our two eyes to determine distance, color, and shape, among other features. The same principle is applied to the image-recognition algorithms, says [Jun] Tanida." May 22, 2007: Google snaps up Stanford robotics - Licensing deal for sensing technology seen as weapon in battle with Microsoft for 3-D mapping services. By Elise Ackerman. ContraCostaTimes.com. "MediaNews has learned that Google has quietly licensed the sensing technology developed by a team of Stanford University students that enabled Stanley, a Volkswagon Touareg R5, to win the 2005 DARPA Grand Challenge. In that race, the Stanford robotic car successfully drove more than 131 miles through the Mojave Desert in less than seven hours. The technology will enable Google to map out photo-realistic 3-D versions of cities around the world, and possibly regain ground it has lost to Microsoft's 3-D mapping application known as Virtual Earth. ... Sebastian Thrun, director of the Stanford Artificial Intelligence Lab and leader of the Stanford Racing Team, will also work part-time at Google." May 21, 2007: I, Coach - What's in Store in Robotics. Someday, robots will do more than vacuum your floors. They'll train you and advise you -- and maybe even help out with the cooking. Gary Anthes interviews Takeo Kanade. Computerworld. "Takeo Kanade is a roboticist, but his work extends far beyond the C3PO-like humanoids that often come to mind when one thinks of robots. He has been a pioneer in computer vision, smart sensors, autonomous land and air vehicles, and medical robotics. Kanade, a professor of computer science and robotics at Carnegie Mellon University in Pittsburgh, recently told Computerworld that people’s notions of what robots can and should do will change. Robots will serve as coaches and advisers, not so much replacing human labor as enhancing it. ... [Q] What’s coming in human-computer interfaces? ...[Q] How could a computer know someone’s intent? [TK] What I’m advocating right now is what I call inside-out vision. ... [Q] Where else might computer vision be applied? ... [Q] What’s next for robotics in manufacturing? ... [Q] What’s the biggest challenge in developing these home robots and the quality-of-life robots? ..." May 11, 2007: The man who taught computers to see - Personal Tech: The world's first digital image. By Steve Woodward. The Oregonian (OregonLive.com). "Russell Kirsch admits it: Inventing square pixels was a bad idea. ... The revolution was born in a moment of inspiration, when Kirsch asked himself a profound question: 'What would happen if a computer could look at the world?' Now that revolution has reached into the arcana of art. Kirsch and his wife, Joan, an art historian, are using computers to reveal the hidden structures of paintings and the artistic processes of the artists who created them. ... In 1957, Kirsch was a computer programmer -- a job category that, at the time, must have seemed closer to magician than to engineer. Kirsch and an elite team worked with SEAC, the Standards Electronic Automatic Computer, the federal government's first electronic programmable computer. He had joined the SEAC team in 1951, a year after the National Bureau of Standards finished building the computer. The team used SEAC to solve government problems in fields as diverse as meteorology, navigation and office automation. But as Kirsch told an oral historian for the National Museum of American History in 1970, he was among a 'fortunate happy few' who also had access to the computer for their own private 'speculative' experiments, such as artificial intelligence and image processing. ... More than 40 years ago, Kirsch became fascinated with the work linguists were doing to detect 'grammars' -- the underlying structures of language. 'I thought, "I bet you can write grammars for pictures,"' he said." May 11, 2007: "Smart cameras" to tackle abandoned luggage alarms. By Mark Trevelyan. Reuters / available from ScientificAmerican.com. "One of the commonest headaches facing security staff may soon be remedied with the help of 'intelligent security cameras' developed by European scientists. A newly concluded research project relies on formulae known as algorithms to enable computers to analyze video images and spot potential threats, from abandoned baggage to people loitering suspiciously. ... 'The idea is to automatically analyze and intelligently filter all of that video, but also to add a next level of intelligence,' said James Ferryman, a specialist in 'computational vision' at the University of Reading in England. 'We're talking about smart cameras which go to the next level of proactive detection.' Mainly funded by the European Union, the two-year, 2.3 million euro ($3.11 million) project involved 10 European companies and research institutes and is known as ISCAPS (Integrated Surveillance of Crowded Areas for Public Security)." May 3, 2007: Police steal cue from 'Knight Rider' - Electronic license plate readers help tag violators. By Chris Barge. Rocky Mountain News. "Aurora Police Lt. Troy Edwards lacks David Hasselhoff's long, curly hair. ... But Edwards is pretty close to living the Knight Rider dream, thanks to a new gizmo that turns cruisers into artificial intelligence machines. ... Growing out of a partnership between gun manufacturer Remington and Italian information technology company Elsag, the Mobile Plate Hunter uses optical character-recognition technology developed for Italian postal workers to sort letters and parcels. The readers tell officers whether a driver's license has been canceled or revoked, if the car or plates are stolen or if there are any warrants out for the driver's arrest." May 2, 2007: Respectful Cameras - A new type of video surveillance protects the privacy of individuals. By Brendan Borrell. Technology Review. "A camera developed by computer scientists at the University of California, Berkeley, would obscure, with an oval, the faces of people who appear on surveillance videos. These so-called respectful cameras, which are still in the research phase, could be used for day-to-day surveillance applications and would allow for the privacy oval to be removed from a given set of footage in the event of an investigation. ... In its current state of development, the camera is only able to obscure the faces of people who are wearing a marker, in the form of a yellow hat or a green vest." May 2, 2007: Mr. Roboto. Astrobiology Magazine. "[A]t MIT, researchers are working on a very early version of such intelligent, robotic helpers--a humanoid called Domo who grasp objects and place them on shelves or counters. ... 'Typically robots are placed in very restricted worlds because then you can control the environment. If you put a robot in someone's home, that approach just doesn't extend to that,' [Aaron Edsinger] said. 'We want the robot to adapt to the world, not the world to adapt to the robot.' ... Domo can 'see' everything going on in front of it. As the robot's large blue eyes roam across the room, cameras feed information to 12 computers that analyze the input and decide what to focus on. ... The philosophy behind the team's approach is that humans and robots can work together to accomplish tasks that neither could do all alone. ... For Domo or any robot to safely interact with humans, the robot has to be able to sense when a human is touching it. Domo has springs in its arms, hands and neck that can sense force and respond to it. If you grab its hand and push, the robot will move the way you want it to. ... The original work on Domo was funded by NASA, and the project is now supported by Toyota, which is interested in developing partner robots for the home. Another application is in assembly line production. The idea is that intelligent robots could work together with people to make workers more productive and save manufacturing jobs from being sent overseas, says Edsinger." April 20, 2007: MIT discovery may improve robotic eyes - How the brain determines texture could improve artificial intelligence visual recognition systems. By Candace Lombardi. CNET News.com. "[Lavanya Sharan] co-authored the paper 'Image statistics and the perception of surface qualities,' which will appear in the April 18 issue of Nature.... 'Practical applications of this work would extend to domestic robots or autonomous vehicles that could understand the world they look at. But it's also important for understanding how human perception works. How the brain understands the color or the shininess of a surface can shed light on the workings of the visual system, which is a large open question,' Sharan said. ... To analyze this process at a more sophisticated level useful to artificial intelligence, the MIT group plotted the process on what Sharan called a 'luminosity histogram.'" April 17, 2007: Man vs machine in football fan battle - Can this computer understand the offside rule? By Steve Ranger. Silicon.com. "Which is a better football fan - man or machine? That's a puzzle BT researchers are working on. The researchers, working at the Adastral Park labs near Ipswich, have developed an algorithm that tries to spot the most interesting bits of a football game - the goals, corners and rows with the ref. ... In the longer term the technology could be used to help computers spot emotions, so a machine could recognise funny or sad parts of a video, for example.[Be sure to see the related video.]
>>> Image Understanding, Vision, Sports, Applications; also see this related NewsToon April 17, 2007: A Robust Robot for the Elderly - Domo the robot is designed for the unpredictability of household chores. By Rachel Ross. Technology Review. "For more than a decade, roboticists have worked on systems for the elderly, hoping to extend the amount of time that seniors can live at home and improve their quality of life. Now MIT researchers have built a humanoid robot with a special motion-tracking system and spring-loaded actuators that make it better equipped to deal with household chores. The robot, named Domo, can size up an object by shaking it in its hand and then put it away in a cupboard. ... The beauty of Domo is that it's a very integrated system and can handle many processes at once. That's why Domo can handle the unexpected; the same algorithm that works for a water bottle will work for a box of spaghetti. ... However, whether a humanoid machine remains the best robotic solution to elder care remains controversial. Sebastian Thrun, director of Stanford's artificial-intelligence lab, questions whether it's necessary for the robot to resemble a human."
>>> Robots, Assisitive Technologies, Household Appliances, Vision, Systems, Applications; also see these related articles April 11, 2007: Google backs character-recognition research. By Caroline McCarthy. CNET News.com. "Google is sponsoring an artificial-intelligence research group's work to develop advanced technologies for character recognition. The open-source project, called Ocropus, has several goals, including developing a high-level, easy-to-use handwriting recognition system that can convert handwritten documents to computer text, assisting in the creation of electronic libraries, analyzing historical documents and helping vision-impaired people access information. The 'ocr' in Ocropus stands for optimal character recognition. The project is headquartered at the Image Understanding and Pattern Recognition (IUPR) research group at the German Research Center for Artificial Intelligence (DFKI) in Kaiserslautern, Germany. DFKI Professor Thomas Breuel is leading the project." April 4, 2007: Getting in Touch - Virtual Maps for the Blind. Tactile models based on video footage could make navigating a new city easier. By Rachel Ross. ScientificAmerican.com. "Researchers in Greece have developed a new system that converts video into virtual, touchable maps for the blind. ... To build the virtual dioramas, the researchers first shoot video of an architectural model. The video is then processed frame by frame using software developed by [Konstantinos] Moustakas' team. As the camera angle changes, the software tracks each structure and determines its shape and location. That data is used to create a three-dimensional grid of force fields for each structure." April 4, 2007: Computer vision - Easy on the eyes. A computer can now recognise classes of things as accurately as a person can. The Economist. "One theory goes that the human brain recognises strategic positions in a general way, and that this helps to reduce the problem to a manageable size. Thomas Serre and his colleagues at the Massachusetts Institute of Technology have built a computer processing system that tries to work in this general way. ... A neuroscientist trying to understand how people recognise objects would thus start with this simplest of systems. That is the purpose of Dr Serre's computer. His project is nothing less than an attempt to reverse-engineer the relevant part of the brain. ... Dr Serre considered his computer's processing units analogous to nerve cells, and he organised them into areas, just as they are in real brains. Then he let the machine learn in much the same way that babies do. ... A system like this has obvious applications (it may, for instance, soon be put to use searching for child-pornography sites on the internet). But it also brings more subtle benefits. Based as it is on how brains work, it may give insights into what happens when they go wrong." April 3, 2007: That face! Those eyes! How recognizable? Technology for computerized facial recognition is improving, according to a recent NIST report. By Wilson P. Dizard III. GCN. "Technology for computerized facial recognition is ten times more accurate now than it was four years ago, and the best of the systems outperform humans, the National Institute of Standards said. The federal government has pressed the private sector to improve facial and iris recognition technology dramatically so as to pave the way for improved biometric systems.... The dramatic performance improvement was one of the goals of the government’s Face Recognition Grand Challenge. 'In an experiment comparing human and algorithm [system] performance, the best-performing face recognition algorithms were more accurate than humans,' NIST reported." March 27, 2007: Firms See ‘Smart’ Closed-Circuit TVs as Good Way to Tap Into Rail, Mass Transit Security. By Matthew M. Johnson. CQ Homeland Security / Congressional Quarterly. "High-tech companies are getting into the business of a reinvigorated technology known as smart CCTV in an effort to cash in on the desire of rail and mass transit operators to guard against terrorist attacks. Instead of putting the burden of isolating suspicious behavior on security workers, the smart closed-circuit TVs can detect anomalies on their own and flash an alert. ... By adding software and computer processors to existing CCTV infrastructure, the systems can be upgraded with an artificial intelligence designed to scan locations for unattended objects, unusual motion and certain kinds of human behavior. ... . The technology holds so much promise that Cathleen Berrick, director of homeland security and justice issues at the Government Accountability Office, recommended that the federal government consider researching it. She made the remark while testifying at a Senate Commerce, Science and Transportation Committee hearing in January." March 26, 2007: Draw, you're on camera. The Engineer Online. "The video surveillance company behind London's congestion charging scheme has announced trials in which CCTV technology will be used to provide real-time information both on board trains and at stations. ... Video surveillance cameras coupled with intelligent algorithms will be used to spot people engaged in graffiti activity at the station." March 26, 2007: Shoulder-worn camera acts as a third eye. By Tom Simonite. NewScientist.com news. "A shoulder-mounted camera system that automatically tracks head movements and can recognise hand gestures has been developed by UK researchers. Eventually, they hope the system could identify a wearer's activity and offer assistance, for example by accessing a telephone directory when they reach for the phone. ... 'If you are going to use wearable computers, you cannot use a computer and mouse,' Mayol Cuevas says." March 26, 2007: For fast-food help, call in the robots - Can artificial intelligence lead to a better drive-through burger? A Pittsburgh-based start-up thinks so. By Michael Kanellos. CNET News.com. "Some robots are destined to rove the surface of Mars. Others, like Hyperactive Bob, will work in fast-food restaurants. Pittsburgh's Hyperactive Technologies has come up with a system, based on the computer vision and artificial intelligence systems employed by robots, to manage the kitchens at so-called quick-service restaurants. ... The Zaxby's chain says it has saved an average of $8,000 in reduced food waste per year. And it sees other benefits as well. 'Your food is fresher because you are cooking small amounts more often,' said Brandi Clanton, who owns two Zaxby's outlets and installed the robot in both. 'Before Bob, they were basically cooking by guesstimate.' [Joe] Porfeli says that some stores have also seen indirect benefits in higher sales and lower employee turnover. ... Both Hyperactive founders are former CMU researchers." March 22, 2007: UCF researchers work on spy drones. By Chris Cobbs. Orlando Sentinel. "A flock of migratory birds can find its way over wide areas of the world. An army of ants working together can devour a large animal. Borrowing from their behavior, two researchers at the University of Central Florida are working to enable droves of small, unmanned aerial vehicles to operate together in an intelligent, coordinated manner, scoping out enemy troops in combat zones. The research is being conducted by College of Engineering and Computer Science professors Mubarak Shah and Niels da Vitoria Lobo, who recently received a grant furthering efforts to program unmanned drones to collect more useful battlefield intelligence. ... 'Our expertise is in automating video data collected by UAVs detecting a threat or determining if some event is happening,' said Shah, director of UCF's Computer Vision Lab." March 19, 2007: MTA takes global perspective on security. By Chuck Bennett,. AM NewYork. "The MTA's top executive is planning to visit transit systems around the world for ideas on making New York's subway and commuter rails a tougher target for terrorists. ... Since the [July 2005] attack, the London Underground began installing closed circuit television cameras with an artificial intelligence component that may be able to recognize suspicious behavior, such as someone hiding a bag under a seat." March 8, 2007: Carnegie Mellon to celebrate accomplishments of robotics pioneer. By David Templeton. Pittsburgh Post-Gazette. "Humans don't see well. Just ask any ophthalmologist. But add in the fact that people embrace illusions, harbor delusions and foster confusion. That's why Takeo Kanade, when he began programming robots to see, decided against using the human model. He developed his own theory of robotic vision that included origami, math and geometry. ... Decades ago, Dr. Kanade created the first complete face-recognition system and first direct-drive robotic arm. Both are still in use. Another famous creation was EyeVision, a system used during broadcast of the 2001 Super Bowl in Tampa that used 51 cameras plus computer software to provide viewers with 'virtualized reality' of action from any angle. Not one to relax, he's now working on an autonomous helicopter. ... Although robots are absent from everyday life, he said, specialized robotic systems have reached the market faster than he anticipated. Future houses might not have humanoid robots but, rather, embedded sensors that can help people complete daily activities. In time, a house will know where its occupants are, what they're doing and how to help them, he said."
>>> Vision, Robots, Smart Houses, Applications, Careers in AI (@ Resources for Students) March 2007: A Robotic Sentry For Korea's Demilitarized Zone. By Jean Kumagai. IEEE Spectrum Online. "Go ahead, make its day. A new gun-toting sentry robot, developed by Samsung Techwin Co. for the South Korean government, may soon be coming to a disputed border near you. The SGR-A1 robot uses a low-light camera and pattern recognition software to distinguish humans from animals or other objects and, if necessary, can fire its built-in machine gun -- a Daewoo K3. ... Should it detect an intruder, 'the ultimate decision about shooting should be made by a human, not the robot,' says [Myung Ho] Yoo, who led the team that designed the robot. But the robot does have an automatic mode, in which it can make the decision. ... By deploying the robots, Yoo thinks his government may be able to significantly reduce the mandatory two years of military service that all young Korean men now serve." February 26, 2007: Watching for Woody, Robot Style. By Brendan Borrell. Wired News. "[T]two computer scientists have created a bird-watching robot to scan the skies for the woodpecker. ... [Ken] Goldberg says since 9/11, advances in machine vision and high-resolution security systems made their robotic bird-watcher possible. ... The robot doesn't identify birds, it simply decides what's a bird and what's not. It's not as easy as it looks. 'That's tricky because birds move very fast and the background is always changing,' Goldberg says. ... ACONE [Automated Collaborative Observatory for Natural Environments] turns thousands of hours of observation into minutes of video that an expert will later review." February 26, 2007: Surveillance cameras get smarter. By Stephen Manning. The Associated Press / available from USATODAY.com. "Look around -- You might not be the only one watching. The never-blinking surveillance cameras, rapidly becoming a part of daily life in public and even private places, may be sizing you up as well. And they may soon get a lot smarter. Researchers and security companies are developing cameras that not only watch the world but also interpret what they see. Soon, some cameras may be able to find unattended bags at airports, guess your height or analyze the way you walk to see if you are hiding something. ... For example, cameras in Chicago and Washington can detect gunshots and alert police. Baltimore installed cameras that can play a recorded message and snap pictures of graffiti sprayers or illegal dumpers. ... Intelligent surveillance uses computer algorithms to interpret what a camera records. The system can be programmed to look for particular things, like an unattended bag or people walking somewhere they don't belong. 'If you think of the camera as your eye, we are using computer programs as your brain,' said Patty Gillespie, branch chief for image processing at the Army Research Laboratory in Adelphi, Md. Today, the military funds much of the smart-surveillance research." February 21, 2007: Biologically Inspired Vision Systems - A computer model of the brain has learned to detect and classify objects. By Duncan Graham-Rowe. Technology review. "Neuroscientists at MIT have developed a computer model that mimics the human vision system to accurately detect and recognize objects in a busy street scene, such as cars and motorcycles. Such biologically inspired vision systems could soon be used in surveillance systems, or in smart sensors that can warn drivers of pedestrians and other obstacles. It may also help in the development of so-called visual search engines, says Thomas Serre, a neuroscientist at the Center for Biological and Computational Learning at MIT's McGovern Institute for Brain Research, who was involved in the project. ... [T]o recognize a particular type of object, such as a car, a computer needs a template or computational representation specific to that particular object. Such a template enables the computer to distinguish a car from objects in other classes--noncars. Yet this representation must be sufficiently flexible to include all types of cars--no matter how varied in appearance--at different angles, positions, and poses, and under different lighting conditions. "... The most effective method for getting around such problems is to train a learning algorithm on a set of images and allow it to extract the features they have in common; two wheels aligned with the road could signal a car, for example. Serre and [Tomaso] Poggio believe that the human vision system uses a similar approach, but one that depends on a hierarchy of successive layers in the visual cortex. " February 20, 2007: Talking bathrooms; System helps Alzheimer's patients look after own hygiene. By Sheryl Ubelacker. Canadian Press / available from the Welland Tribune / also available from globeandmail.com (Artificial intelligence to help dementia sufferers | February 23, 2006). "[R]esearchers at the Toronto Rehab Institute are working on artificial intelligence systems - including a 'smart bathroom' - that they hope will one day help people with Alzheimer's and other forms of dementia live more independent lives in their own homes. 'Often when a person gets moderate to severe levels of impairment, they are taken out of their home and put into a care facility,' said lead researcher Dr. Alex Mihailidis, a mechanical and biomedical engineer at Toronto Rehab. 'We are using artificial intelligence to support aging-in-place so that people can remain in their homes for as long as possible.' ... Mihailidis and his team have also designed prototype technology to detect when a person has fallen." February 19, 2007: Robot birdwatcher joins hunt for elusive woodpecker. By Gaia Vince. New Scientist News. "Ornithologists seeking the elusive ivory-billed woodpecker have been given a much needed boost: the world's first fully automated, robotic birdwatcher. ... The system has two video cameras that photograph the sky at 22 frames per second. This stream of images is rapidly screened for birds flying overhead using computer vision algorithms. ... The next challenge is to develop the system so it can be used to monitor trees and forest floors. For that, more sophisticated algorithms will be required, capable of distinguishing a passing animal from swaying branch or plant."
>>> Vision, Robots, Applications; and speaking of birdwatching, check out our Bird Watcher's Field Guide to Reasoning February 17, 2007: Stanford team readies robotic vehicle for city street race. By Matt Nauman. The Mercury News. "About 90 teams have signed up for the third Grand Challenge, to be called the Urban Challenge, in November. The race requires all vehicles to be autonomous -- they're not operated via remote control or with any other human contact, interference or direction. The 2005 winner, the Stanford Racing Team that combined artificial-intelligence academics from the university, vehicle engineers from Volkwagen's Silicon Valley R&D lab in Palo Alto, and the deep pockets of a Sand Hill Road venture capital firm, is back. So, too, are parts of another team of tech-minded dreamers who called themselves Team Underdawg. ... The Grand Challenge event evolved from a congressional mandate that one-third of ground combat vehicles be unmanned by 2015. ... 'We'd certainly enjoy winning, but our goal first and foremost is to perform research that moves forward the idea of autonomous vehicles,' [Jonathan Sprinkle, executive director of UC-Berkeley's Center for Hybrid and Embedded Software Systems] said."
>>> Grand Challenges, Autonomous Vehicles, Military, Transportation, Vision, Competitions (@ Resources for Students), Robots February 16, 2007: Deaf to sign via video handsets. BBC News. "Video compression tools made by US researchers make it possible to send live pictures of people signing across low bandwidth mobile networks. The system cuts down on the bandwidth needed by only sending data about which parts of each frame have changed. ... [T]he system developed by Prof Ladner and his co-workers only looks for hand, arm and face movements. In addition it ensures that the face of a signer, where movements during signing are quite subtle, is presented in more detail." February 11, 2007: 'Intelligent' homes designed to help the elderly. CTV.ca. "Scientists in Toronto say they have are developing artificially intelligent computer systems to help elderly people suffering from memory loss stay safely in their own homes. 'Often when a person gets moderate to severe levels of impairment, they are taken out of their home and put into a care facility,' says lead scientist Dr. Alex Mihailidis, a mechanical and biomedical engineer and researcher at Toronto Rehabilitation Institute. 'We are using artificial intelligence to support aging-in-place so that people can remain in their homes for as long as possible.' ... 'Our systems are not intended to replace professional or family caregivers. However, the results from our studies are encouraging and show that the use of artificial intelligence in a home setting can provide safety and security and enhance the quality of life for older adults who would like to remain in their homes as they age,' Mihailidis said. This could also assist those giving informal care to loved ones." February 6, 2007: Mimicking How the Brain Recognizes Street Scenes. CCNmag.com. "At last, neuroscience is having an impact on computer science and artificial intelligence (AI). For the first time, scientists in Tomaso Poggio’s laboratory at the McGovern Institute for Brain Research at MIT applied a computational model of how the brain processes visual information to a complex, real world task: recognizing the objects in a busy street scene. The researchers were pleasantly surprised at the power of this new approach. ... 'People have been talking about computers imitating the brain for a long time,' said Poggio, who is also the Eugene McDermott Professor in the Department of Brain and Cognitive Sciences and the co-director of the Center for Biological and Computational Learning at MIT. 'That was Alan Turing’s original motivation in the 1940s. But in the last 50 years, computer science and AI have developed independently of neuroscience. Our work is biologically inspired computer science.' ... Near-term applications include surveillance and automobile driver’s assistance, and eventually visual search engines, biomedical imaging analysis, robots with realistic vision." January 25, 2007: Artificially intelligent homes for Alzheimer's patients coming: scientists. CBC News. "Scientists in Toronto are developing an artificial intelligence system that would help people with Alzheimer's disease or other cognitive impairments live safely at home.The Toronto Rehabilitation Institute is working with University of Toronto researchers to make home-based computer systems that would assist elderly people with memory loss in living independently. ... [L]ead scientist Alex Mihailidis said in a written statement. 'We are using artificial intelligence to support aging-in-place so that people can remain in their homes for as long as possible.' ... The researchers have also created a home emergency alert system that uses ceiling-mounted cameras linked to computers running image analysis software to determine whether a person has fallen down. It would then ask whether he or she needs help and use a voice-recognition system to process a response. ... The researchers say they are the first in the world to test home-based artificial intelligence systems in clinical trials." January 17, 2007: Walking like a Bomber - New strides in radar and gait-analysis software show that it's possible to detect when someone is carrying a bomb well before he or she reaches a security checkpoint. By Karen Nitkin. Technology Review. "A new radar-imaging technology expected to reach market later this year could solve the problem by directing low-power radar beams at people--who can be 50 yards or more away--and analyzing reflected radar returns to reveal concealed objects. And early research indicates that this method could one day be augmented with video-analysis software that spots bombers by discerning subtle differences in gait that occur when people carry heavy objects. ... [T]his technology is helped by novel technology that tracks the subject--thereby enabling the radar to be continuously aimed at the moving person. Software developed by Rama Chellappa, a professor in the department of electrical and computer engineering and a member of the University of Maryland's Institute for Advanced Computer Studies, uses a form of 'gait recognition' to do this. It notes a person's walking style and physical attributes such as height, then uses those features to follow individuals as they move and locate them again even after they've been obscured by poles or other objects. ... But the next generation of Chellappa's technology could extend the role of gait recognition. In early-stage research, he has shown that he can analyze the joint movements of a walking person and tell whether those movements are anomalous and possibly consistent with carrying heavy objects--and even whether the person has just deposited something on the ground." January 5, 2007: Watch & learn - By analyzing a person's body language, gait and other movements, behavior recognition software is helping catch criminals and may be useful in the war on terror, as well as have medical applications. By Frank D. Roylance. baltimoresun.com. "Behavior recognition software enables computers to alert people when something, or someone, appears suspicious. The [Johns Hopkins University] system employs one application of the technology to watch for aberrant movements captured by dozens of cameras - far more than any person could track. Computer analysis of the way people and objects appear and move on video is also being developed at the University of Maryland's A. James Clark School of Engineering and elsewhere for use in surveillance, security, anti-terrorism and even medical applications. ... Some Americans might also want to ask whether this sort of public surveillance and scrutiny is a good thing, or a threat to privacy. ... In 2000, [Rama] Chellappa began working on gait recognition with Mark Nixon of the University of Southampton in England. They developed computer programs, using algorithms that convert digital video data to mathematical patterns. The software analyzes whether patterns generated by an individual's movements match those designated as suspicious." January 4, 2007: Software upgrade makes Mars rovers smarter for third anniversary. By Alicia Chang. The Associated Press / available from The Desert Sun. "The twin Mars rovers are getting wiser with age. Engineers have transmitted new flight software to the rovers' onboard computers - just in time for the third anniversary of their landings. The software is aimed at boosting their intelligence and independence so that they can roll around the Red Planet with less help from humans. ... Among the rovers' new skills is the ability to automatically recognize and transmit to Earth photographs that they take of swirling dust devils or floating clouds. They can also independently decide whether it is safe to extend their robotic arms to sample rocks." January 3, 2007: Analysis - Hot Technology in 2007. By Mike Elgan. Digit Online. "The year of face recognition - Face-recognition technology will be red-hot this year, and will show up in a growing number of consumer products and services, including digital cameras, online photo search engines and biometric security devices. One of the most exciting new features in an increasing number of consumer digital cameras this year will be face recognition -- or, more accurately, face detection. Artificial intelligence software onboard these cameras knows the difference between a human face and other objects in the shot." January 2, 2007: Mars rovers are taught new tricks - Nasa is testing a "smart" upgrade to its robotic rovers on Mars. BBC News. "Space agency scientists have begun testing four new skills included in flight software that has been uploaded to the rovers' onboard computers. The two American rovers, Spirit and Opportunity, are approaching their third year on the Martian surface. One of the new capabilities is designed to allow the rovers to make 'intelligent' decisions in the study of Martian clouds and dust devils." January 1, 2007: Factories of the Future - Machines that "see" parts on assembly lines, 3-D printers that prototype products in hours -- let's take a look at adaptive manufacturing. Editorial by Fred Hapgood. CIO. "What kinds of technology will enable an adaptive manufacturing environment? Machine vision is an important example of the sort of technology that is converting manufacturing into an information-based process. Machine vision does not mean recording or registering a raw image, as a camera would, but recognizing the actual objects in an image and assigning properties to those objects -- understanding what they mean. Vision in this sense makes every aspect of manufacturing -- inventory, transport, tooling and assembly operations -- much more efficient. ... [M]achine vision is a real industry. The consultancy Vision Systems International pegs the total value of the North American market at around $1.5 billion. ... The Chicago Museum of Science and Industry uses Fanuc robots with machine vision to let museum-goers design their own toy (a top), which the robots then build while they watch. ... Both machine vision and 3DP sit inside the realm of ambitious new manufacturing technologies: high-resolution sensor and actuator networks."
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