Moving object tracking in video

Yiwei Wang, John F. Doherty, Robert E. Van Dyck

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

41 Scopus citations

Abstract

The advance of technology makes video acquisition devices better and less costly, thereby increasing the number of applications that can effectively utilize digital video. Compared to still images, video sequences provide more information about how objects and scenarios change over time. However, video needs more space for storage and wider bandwidth for transmission. Hence is raised the topic of video compression. The MPEG 4 compression standard suggests the usage of object planes. If the object planes are segmented correctly and the motion parameters are derived for each object plane accordingly, a better compression ratio can be expected. Therefore, to take full advantage of the MPEG 4 standard, algorithms for tracking objects are needed. It is also obvious that there is great interest in moving object tracking algorithms in the fields of reconnaissance, robot technology, etc. So, we propose an algorithm to track moving objects in video sequences. The algorithm first separates the moving objects from the background in each frame. Then, four sets of variables are computed based on the positions, the sizes, the grayscale distributions and the presence of textures of the objects. A rule-based method is developed to track the objects between frames, based on the values of the variables. Preliminary experimental results show that the algorithm performs well. The tests also show that the algorithm obtains success in indicating new tracks (object starts moving), ceased tracks (object stops moving) and possible collisions (objects move together).

Original languageEnglish (US)
Title of host publicationProceedings - 29th Applied Imagery Pattern Recognition Workshop
Subtitle of host publication"Imagery in the New Millennium", AIPR 2000
EditorsJames V. Aanstoos
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages95-101
Number of pages7
ISBN (Electronic)0769509789
DOIs
StatePublished - 2000
Event29th Applied Imagery Pattern Recognition Workshop, AIPR 2000 - Washington, United States
Duration: Oct 16 2000Oct 18 2000

Publication series

NameProceedings - Applied Imagery Pattern Recognition Workshop
Volume2000-January
ISSN (Print)2164-2516

Other

Other29th Applied Imagery Pattern Recognition Workshop, AIPR 2000
Country/TerritoryUnited States
CityWashington
Period10/16/0010/18/00

All Science Journal Classification (ASJC) codes

  • General Engineering

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