Human activity recognition from frame's spatiotemporal representation

Zhipeng Zhao, Ahmed Elgammal

Research output: Chapter in Book/Report/Conference proceedingConference contribution

10 Scopus citations

Abstract

This paper presents an approach for human activity recognition by representing the frames of the video sequence with the distribution of local motion features and their spatiotemporal arrangements. In this approach, the local motion features used for the representation of a frame are integrated from the ones detected in this frame and its temporal neighbors. The features' spatial arrangements are captured in a hierarchical spatial pyramid structure. By using frame by frame voting for the recognition, experiments have demonstrated improved performances over most of the other known methods on the popular benchmark data sets while approaching the best known results.

Original languageEnglish (US)
Title of host publication2008 19th International Conference on Pattern Recognition, ICPR 2008
StatePublished - 2008
Event2008 19th International Conference on Pattern Recognition, ICPR 2008 - Tampa, FL, United States
Duration: Dec 8 2008Dec 11 2008

Publication series

NameProceedings - International Conference on Pattern Recognition
ISSN (Print)1051-4651

Other

Other2008 19th International Conference on Pattern Recognition, ICPR 2008
CountryUnited States
CityTampa, FL
Period12/8/0812/11/08

All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition

Fingerprint Dive into the research topics of 'Human activity recognition from frame's spatiotemporal representation'. Together they form a unique fingerprint.

Cite this