A biologically inspired system for action recognition

H. Jhuang*, T. Serre, L. Wolf, T. Poggio

*Corresponding author for this work

Research output: Contribution to conferencePaperpeer-review

621 Scopus citations

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 motion-direction 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.

Original languageEnglish
DOIs
StatePublished - 2007
Event2007 IEEE 11th International Conference on Computer Vision, ICCV - Rio de Janeiro, Brazil
Duration: 14 Oct 200721 Oct 2007

Conference

Conference2007 IEEE 11th International Conference on Computer Vision, ICCV
Country/TerritoryBrazil
CityRio de Janeiro
Period14/10/0721/10/07

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