Global motion compensation for image sequences and motion object detection

A effective approach to global motion compensation and moving object extraction is proposed. Firstly, feature-block detection and search-matching algorithm are used to attain background motion vectors of global image. Then, once the global motion vectors are robustly estimated, relatively stationary background can be almost completely eliminated through the registration difference algorithm. Finally, higher-order statistics is used to attain the motion target exactly. The experimental results validate that the proposed algorithm improves the performance of detection moving targets and effectively restrains the noise disturbance.

[1]  Xiangzhi Bai,et al.  Moving Vehicles Detection in Airborne Video , 2008, 2008 International Symposium on Information Science and Engineering.

[2]  Chok-Kwan Cheung,et al.  Adaptive motion tracking block matching algorithms for video coding , 1999, IEEE Trans. Circuits Syst. Video Technol..

[3]  Yang Zhi.  An Investigation on Background Moving Compensation , 2000 .

[4]  S. K. Satyanarayana,et al.  Predictive Search Range and Block Size in Block Matching Motion Estimation Algorithms in Video Coding , 2009, 2009 2nd International Congress on Image and Signal Processing.

[5]  Alessandro Neri,et al.  Automatic moving object and background separation , 1998, Signal Process..

[6]  Zhenya He,et al.  Video object segmentation based on HOS and multi-resolution watershed , 2004, Proceedings of 2004 International Symposium on Intelligent Multimedia, Video and Speech Processing, 2004..

[7]  Li Chun-ming,et al.  Moving object extraction algorithm and its application , 2005 .

[8]  Zhang Xiaohu.  Moving targets real-time detecting methods based on the image sequences , 2004 .

[9]  Bing Zeng,et al.  A new three-step search algorithm for block motion estimation , 1994, IEEE Trans. Circuits Syst. Video Technol..

[10]  T Koga,et al.  MOTION COMPENSATED INTER-FRAME CODING FOR VIDEO CONFERENCING , 1981 .

[11]  Chongzhao Han,et al.  Motion estimation based on an improved block matching technique , 2006 .

[12]  Sarp Erturk,et al.  Block motion estimation using adaptive modified two-bit transform , 2007 .

[13]  Yan Li,et al.  Moving Objects Detection in Birds Video Based on Multiple Block Matching , 2009, 2009 Fourth International Conference on Computer Sciences and Convergence Information Technology.

[14]  Jong-Nam Kim,et al.  A fast three-step search algorithm with minimum checking points using unimodal error surface assumption , 1998 .

[15]  Jae Wook Jeon,et al.  Background compensation using Hough transformation , 2008, 2008 IEEE International Conference on Robotics and Automation.