Biometrics Driven Smart Environments: Abstract Framework and Evaluation
UIC '08 Proceedings of the 5th international conference on Ubiquitous Intelligence and Computing
Actively exploring creation of face space(s) for improved face recognition
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
Multimodal identification and tracking in smart environments
Personal and Ubiquitous Computing
Active learning for on-road vehicle detection: a comparative study
Machine Vision and Applications
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This paper describes a method by which a computer can autonomously acquire training data for learning to recognize a user's face. The computer, in this method, actively seeks out opportunities to acquire informative face examples. Using the principles of co-training, it combines a face detector trained on a single input image with tracking to extract face examples for learning. Our results show that this method extracts well-localized, diverse face examples from video after being introduced to the user through only one input image. In addition to requiring very little human intervention, a second significant benefit to this method is that it doesn't rely on a statistical classifier trained on a preexisting face database for face detection. Because it doesn't require pre-training, this method has built-in robustness for situations where the application conditions differ from the conditions under which training data were acquired.