Virtual gazing in video surveillance

Yingzhen Yang, Yang Cai

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

1 Scopus citations

Abstract

Although a computer can track thousands of moving objects simultaneously, it often fails to understand the priority and the meaning of the dynamics. Human vision, on the other hand, can easily track multiple objects with saccadic motion. The single thread eye movement allows people to shift attention from one object to another, enabling visual intelligence from complex scenes. In this paper, we present a motion-context attention shift (MCAS) model to simulate attention shifts among multiple moving objects in surveillance videos. The MCAS model includes two modules: The robust motion detector module and the motion-saliency module. Experimental results show that the MCAS model successfully simulates the attention shift in tracking multiple objects in surveillance videos.

Original languageEnglish (US)
Title of host publicationSMVC'10 - Proceedings of the 2010 ACM Workshop on Surreal Media and Virtual Cloning, Co-located with ACM Multimedia 2010
Pages15-20
Number of pages6
DOIs
StatePublished - 2010
Externally publishedYes
Event2010 ACM Workshop on Surreal Media and Virtual Cloning, SMVC'10, Co-located with ACM Multimedia 2010 - Firenze, Italy
Duration: Oct 29 2010Oct 29 2010

Publication series

NameSMVC'10 - Proceedings of the 2010 ACM Workshop on Surreal Media and Virtual Cloning, Co-located with ACM Multimedia 2010

Conference

Conference2010 ACM Workshop on Surreal Media and Virtual Cloning, SMVC'10, Co-located with ACM Multimedia 2010
CountryItaly
CityFirenze
Period10/29/1010/29/10

Keywords

  • Motion detector
  • Motion-context attention shift
  • Motion-saliency module
  • Simulation
  • Virtual gazing

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Graphics and Computer-Aided Design
  • Human-Computer Interaction

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