Moving objects extraction method in H.264/advanced video coding bit stream of a complex scene

Mingsheng Chen; Mingxin Qin; Guangming Liang; Jixiang Sun; Xu Ning

doi:10.1117/1.OE.52.8.083107

9 August 2013 Moving objects extraction method in H.264/advanced video coding bit stream of a complex scene

Mingsheng Chen, Mingxin Qin, Guangming Liang, Jixiang Sun, Xu Ning

Author Affiliations +

Optical Engineering, Vol. 52, Issue 8, 083107 (August 2013). https://doi.org/10.1117/1.OE.52.8.083107

Abstract

For the purpose of extracting moving objects from H.264/advanced video coding (AVC) bit stream of a complex scene, an algorithm based on maximum a posteriori Markov random field (MRF) framework to extract moving objects directly from H.264 compressed video is proposed in this paper. It mainly involves encoding information of motion vectors (MVs) and block partition modes in H.264/AVC bit stream and utilizes temporal continuity and spatial consistency of moving object’s pieces. First, it retrieves MVs and block partition modes of identical 4×4 pixel blocks in P frames and establishes Gaussian mixture model (GMM) of the phase of MVs as a reference background, and then creates MRF model based on MVs, block partition modes, the GMM of the background, spatial, and temporal consistency. The moving objects are retrieved by solving the MRF model. The experimental results show that it can perform robustly in a complex environment and the precision and recall have been improved over the existing algorithm.

Citation Download Citation

Mingsheng Chen, Mingxin Qin, Guangming Liang, Jixiang Sun, and Xu Ning "Moving objects extraction method in H.264/advanced video coding bit stream of a complex scene," Optical Engineering 52(8), 083107 (9 August 2013). https://doi.org/10.1117/1.OE.52.8.083107

Published: 9 August 2013

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

;

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE