Video Compression and Retrieval of Moving Object Location Applied to Surveillance

  • Authors:
  • William Robson Schwartz;Helio Pedrini;Larry S. Davis

  • Affiliations:
  • Department of Computer Science, University of Maryland, College Park, USA 20742;Institute of Computing, University of Campinas, Campinas, Brazil 13084-971;Department of Computer Science, University of Maryland, College Park, USA 20742

  • Venue:
  • ICIAR '09 Proceedings of the 6th International Conference on Image Analysis and Recognition
  • Year:
  • 2009

Quantified Score

Hi-index 0.00

Visualization

Abstract

A major problem in surveillance systems is the storage requirements for video archival; videos are recorded continuously for long periods of time, resulting in large amounts of data. Therefore, it is essential to apply efficient compression techniques. Additionally, it is useful to be able to index the archived videos based on events. In general, such events are defined by the interaction among moving objects in the scene. Consequently, besides data compression, efficient ways of storing moving objects should be considered. We present a method that exploits both temporal and spatial redundancy of videos captured from static cameras to perform compression and subsequently allows fast retrieval of moving object locations directly from the compressed data. Experimental results show that the approach achieves high compression ratios compared to other existing video compression techniques without significant quality degradation and is fast due to the simplicity of the operations required for compression and decompression.