Motion information combination for fast human action recognition

Hongying Meng, Nick Pears, Chris Bailey

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

Abstract

In this paper, we study the human action recognition problem based on motion features directly extracted from video. In order to implement a fast human action recognition system, we select simple features that can be obtained from non-intensive computation. We propose to use the motion history image (MHI) as our fundamental representation of the motion. This is then further processed to give a histogram of the MHI and the Haar wavelet transform of the MHI. The processed MHI thus allows a combined feature vector to be computed cheaply and this has a lower dimension than the original MHI. Finally, this feature vector is used in a SVM-based human action recognition system. Experimental results demonstrate the method to be efficient, allowing it to be used in real-time human action classification systems.

Original languageEnglish
Title of host publicationVISAPP 2007: Proceedings of the Second International Conference on Computer Vision Theory and Applications, Volume IU/MTSV
EditorsAK Ranchordas, H Araujo, J Vitria
Place of PublicationSETUBAL
PublisherINSTICC-INST SYST TECHNOLOGIES INFORMATION CONTROL & COMMUNICATION
Pages21-28
Number of pages8
ISBN (Print)978-972-8865-74-0
Publication statusPublished - 2007
Event2nd International Conference on Computer Graphics Theory and Applications - Barcelona
Duration: 8 Mar 200711 Mar 2007

Conference

Conference2nd International Conference on Computer Graphics Theory and Applications
CityBarcelona
Period8/03/0711/03/07

Keywords

  • event recognition
  • human action recognition
  • video analysis
  • support vector machine

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