Moving objects segmentation in video sequence based on Bayesian network

Thach Thao Duong, Anh Duc Duong

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper proposes an improvement over moving objects segmentation method for video sequence based on Bayesian network. The method integrates temporal and spatial features by Bayesian network through three fields, which are motion vector field, intensity segmentation field and object video segmentation field. Markov random field aims to push the spatial connectivity between regions. The improvement concentrates on the MAP estimation procedure in order to obtain the exact segmentation results. The Iterative MAP Estimation may cause much more error in estimation procedure and degrade the convergence of the algorithm. This paper proposes a non-iterative Estimation as an improvement for this algorithm. The non-iterative MAP estimation does not need the previous segmentation result. Therefore, the inaccurate segmentation result of former stage does not have effect on the current segmentation stage. Additionally, the non-iterative MAP estimation was designed to adapt the original model so that it does not cause failure from the theory. Experiments show that the improvement is better than the original version and has good results in some benchmark video sequences.

Original languageEnglish
Title of host publication2010 IEEE-RIVF International Conference on Computing and Communication Technologies
Subtitle of host publicationResearch, Innovation and Vision for the Future, RIVF 2010
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781424480753
ISBN (Print)9781424480746
DOIs
Publication statusPublished - 2010
Externally publishedYes
Event2010 8th IEEE-RIVF International Conference on Computing and Communication Technologies: Research, Innovation and Vision for the Future, RIVF 2010 - Hanoi, Viet Nam
Duration: 1 Nov 20104 Nov 2010

Publication series

Name2010 IEEE-RIVF International Conference on Computing and Communication Technologies: Research, Innovation and Vision for the Future, RIVF 2010

Conference

Conference2010 8th IEEE-RIVF International Conference on Computing and Communication Technologies: Research, Innovation and Vision for the Future, RIVF 2010
Country/TerritoryViet Nam
CityHanoi
Period1/11/104/11/10

Keywords

  • Bayesian network
  • MAP estimation
  • Markov random field
  • Moving objects
  • Video segmenation

Fingerprint

Dive into the research topics of 'Moving objects segmentation in video sequence based on Bayesian network'. Together they form a unique fingerprint.

Cite this