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Automatic acquisition of exemplar-based representations for recognition from image sequences

MPG-Autoren
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Wallraven,  C
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Bülthoff,  HH
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Zitation

Wallraven, C., & Bülthoff, H. (2001). Automatic acquisition of exemplar-based representations for recognition from image sequences. In T. Kanade, & T. Sim (Eds.), CVPR 2001 Workshop on Models versus Exemplars in Computer Vision (pp. 1-9).


Zitierlink: https://hdl.handle.net/11858/00-001M-0000-0013-E160-5
Zusammenfassung
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 `key-frames' 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.