Automatic acquisition of exemplar-based representations for recognition from image sequences
نویسنده
چکیده
We present an exemplar-based object recognition system which is capable of on-line learning of representations of scenes and objects from image sequences. Local appearance features are used in a tracking framework to find ‘keyframes’ of the input sequence during learning. The representation of the stored sequences which are used for recognition of novel images consists only of the appearance features in these key-frames and contains no further a-priori assumptions about the underlying sequences. The system is able to create sparse and extendable representations and shows good recognition performance in a variety of viewing conditions for databases of natural and synthetic image sequences.
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