OPTIMOL: A Framework For Online Picture Collection Via Incremental Model Learning

Li-Jia Li, Juan Carlos Niebles, Li Fei-Fei

OPTIMOL is a novel, automatic dataset collecting and model learning system for object categorization. Our algorithm mimics the human learning process in such a way that, starting from a few training examples, the more confident data you incorporate in the training data, the more reliable models can be learnt. Our system uses the Internet as the (nearly) unlimited resource for images. The learning and image collection processes are done via an iterative and incremental scheme. The goal of this work is to use this tremendous web resource to learn robust object category models in order to detect and search for objects in real-world scenes.

Subjects: 19. Vision; 12. Machine Learning and Discovery

Submitted: Apr 26, 2007

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