Bayesian method for motion segmentation and tracking in compressed videos

Journal article
(Report)


Publication Details

Author(s): Treetasanatavorn S, Rauschenbach U, Heuer J, Kaup A
Editor(s): Kropatsch W.G.; Sablating R.; Hanbury A.
Journal: Computer Science
Publication year: 2005
Volume: 3663
Pages range: 277-284
ISSN: 1508-2806
Language: English


Abstract


This contribution presents a statistical method for segmentation and tracking of moving regions from the compressed videos. This technique is particularly efficient to analyse and track motion segments from the compression-oriented motion fields by using the Bayesian estimation framework. For each motion field, the algorithm initialises a partition that is subject to comparisons and associations with its tracking counterpart. Due to potential hypothesis incompatibility, the algorithm applies a conflict resolution technique to ensure that the partition inherits relevant characteristics from both hypotheses as far as possible. Each tracked region is further classified as a background or a foreground object based on an approximation of the logical mass, momentum, and impulse. The experiment has demonstrated promising results based on standard test sequences. © Springer-Verlag Berlin Heidelberg 2005.


FAU Authors / FAU Editors

Kaup, André Prof. Dr.-Ing.
Lehrstuhl für Multimediakommunikation und Signalverarbeitung


How to cite

APA:
Treetasanatavorn, S., Rauschenbach, U., Heuer, J., & Kaup, A. (2005). Bayesian method for motion segmentation and tracking in compressed videos. Computer Science, 3663, 277-284. https://dx.doi.org/10.1007/11550518_35

MLA:
Treetasanatavorn, Siripong, et al. "Bayesian method for motion segmentation and tracking in compressed videos." Computer Science 3663 (2005): 277-284.

BibTeX: 

Last updated on 2019-10-06 at 14:50