Abstract
We present an object recognition system which is capable of on-line learning of representations of scenes and objects from natural image sequences. Local appearance features are used in a tracking framework to find ‘key-frames’ of the input sequence during learning. In addition, the same basic framework is used for both learning and recognition. The system creates sparse representations and shows good recognition performance in a variety of viewing conditions for a database of natural image sequences.
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© 2001 Springer-Verlag Berlin Heidelberg
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Wallraven, C., Bülthoff, H. (2001). Acquiring Robust Representations for Recognition from Image Sequences. In: Radig, B., Florczyk, S. (eds) Pattern Recognition. DAGM 2001. Lecture Notes in Computer Science, vol 2191. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45404-7_29
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DOI: https://doi.org/10.1007/3-540-45404-7_29
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