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A biologically inspired system for action recognition (2007)
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| Venue: | In ICCV |
| Citations: | 236 - 14 self |
BibTeX
@INPROCEEDINGS{Jhuang07abiologically,
author = {H. Jhuang and T. Serre and L. Wolf and T. Poggio},
title = {A biologically inspired system for action recognition},
booktitle = {In ICCV},
year = {2007},
pages = {1--8}
}
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Abstract
We present a biologically-motivated system for the recognition of actions from video sequences. The approach builds on recent work on object recognition based on hierarchical feedforward architectures [25, 16, 20] and extends a neurobiological model of motion processing in the visual cortex [10]. The system consists of a hierarchy of spatio-temporal feature detectors of increasing complexity: an input sequence is first analyzed by an array of motiondirection sensitive units which, through a hierarchy of processing stages, lead to position-invariant spatio-temporal feature detectors. We experiment with different types of motion-direction sensitive units as well as different system architectures. As in [16], we find that sparse features in intermediate stages outperform dense ones and that using a simple feature selection approach leads to an efficient system that performs better with far fewer features. We test the approach on different publicly available action datasets, in all cases achieving the highest results reported to date. 1.
Keyphrases
action recognition inspired system video sequence processing stage efficient system sparse feature input sequence different system architecture recent work biologically-motivated system visual cortex dense one simple feature selection approach available action datasets motion processing hierarchical feedforward spatio-temporal feature detector object recognition intermediate stage different type position-invariant spatio-temporal feature detector motiondirection sensitive unit neurobiological model motion-direction sensitive unit
