Adaptive background-updating and target detection in motion state - Details

Author：

Mao, Zheng (Mao, Zheng.) | Gao, Anjie (Gao, Anjie.) | Wei, Wei (Wei, Wei.) | Sun, Legong (Sun, Legong.) | Chen, Silin (Chen, Silin.)

Indexed by：

EI Scopus

Abstract：

A　common　method　for　moving　target　detection　in　image　sequences　involves　a　self-adaptive　threshold　for　segmentation.　This　paper　discusses　each　pixel　modeling　in　the　image　as　a　mixture　of　Gaussian　distributions　and　gives　an　improved　method　to　update　the　model.　First,　the　characteristics　of　the　different　frames　method　and　a　mixture　of　Gaussian　distributions　will　be　discussed.　And　then,　the　two　methods,　different　frames　method　and　a　mixture　of　Gaussian　distributions　are　combined　to　decide　which　learning　rate　is　suitable　for　the　updating　method　at　this　moment.　If　there　is　no　moving　target　in　the　image　sequences,　the　background　model　should　be　updated　quickly　to　get　the　real　background　with　low　noise.　The　better　foreground　images　will　be　gotten　by　this　method　with　low　computational　complexity.　The　improved　algorithm　performs　more　robustly　and　powerfully　than　the　classical　Gaussian　Mixture　Model　in　moving　target　detecting.　©　2011　Springer-Verlag.

Keyword：

Target tracking Motion analysis Image enhancement Image segmentation Object recognition Robotics Gaussian distribution

Author Community：

[ 1 ] [Mao, Zheng]School of Electronic Information and Control Engineering, Beijing University of Technology, Beijing, 100124, China
[ 2 ] [Gao, Anjie]School of Electronic Information and Control Engineering, Beijing University of Technology, Beijing, 100124, China
[ 3 ] [Wei, Wei]Northwest Mechanical and Electrical Engineering Institute, Xianyang, Shaaxi, 712099, China
[ 4 ] [Sun, Legong]School of Electronic Information and Control Engineering, Beijing University of Technology, Beijing, 100124, China
[ 5 ] [Chen, Silin]School of Electronic Information and Control Engineering, Beijing University of Technology, Beijing, 100124, China