Examination of a tracking and detection method using compressed domain information

Erii Maekawa, Satoshi Goto

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

7 Citations (Scopus)

Abstract

In this paper, we propose a moving object tracking method in the compressed domain. Because video data are large in size, it is usually compressed by H.264/AVC or MPEG for storage or transmission. Most image processing systems track targets in the pixel domain after decoding compressed data. Objects in video data are tracked based on their color and luminance information in the pixel domain. However, tracking methods in the pixel domain have higher computational complexity than in the compressed domain. We propose a method that directly employs moving object tracking in the compressed domain without a decoding process. Tracking algorithms in the compressed domain are usually based on motion information, or motion vectors. However, motion vectors are not generated when objects stop moving, and their accuracy is low. To overcome these problems, we propose a method that uses motion vectors and other information in macroblocks to track moving objects in a compressed H.264/AVC video stream. The proposed method can reduce computational complexity compared to a pixel domain algorithm. In addition, experimental results show that tracking accuracy is improved by the proposed method. Therefore, this method can be effectively used for video surveillance systems.

Original languageEnglish
Title of host publication2013 Picture Coding Symposium, PCS 2013 - Proceedings
PublisherIEEE Computer Society
Pages141-144
Number of pages4
ISBN (Print)9781479902941
DOIs
Publication statusPublished - 2013
Event2013 Picture Coding Symposium, PCS 2013 - San Jose, CA
Duration: 2013 Dec 82013 Dec 11

Other

Other2013 Picture Coding Symposium, PCS 2013
CitySan Jose, CA
Period13/12/813/12/11

Keywords

  • Motion detection
  • Video compression
  • Video signal processing

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Software

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