loading...
Moving Obstacles Extraction with Stereo Global Motion Model
Hong Kong August 20-August 24
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICPR.2006.82018th International Conference on Patt ...
 This Article 
 
PDF
HTML
 
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
Zhencheng Hu, Kumamoto University, Japan
Keiichi Uchimura, Kumamoto University, Japan
Jia Wang, NEC Labs, China
Extraction of moving obstacles from a moving observer is vital for many ITS applications like Forward Vehicle Collision Mitigation (FVCM) and Adaptive Cruise Control (ACC) systems. Single camera based Global Motion Model (GMM) like optical flow is commonly used in the past decade. This paper addresses a relatively new problem in the literature: GMM based on binocular stereovision which involves the depth (disparity) information in the model, thus global motion can be analyzed in 3D space rather than the traditional 2D image plane. An efficient algorithm is presented which parameterizes the GMM based on the 3D camera motion analysis within U-V-disparity domain. Combining the geometric and motion information, regions that do not match the GMM will be extracted as moving obstacles.
Citation:
Zhencheng Hu, Keiichi Uchimura, Jia Wang, "Moving Obstacles Extraction with Stereo Global Motion Model," icpr, vol. 1, pp.79-83, 18th International Conference on Pattern Recognition (ICPR'06) Volume 1, 2006
Usage of this product signifies your acceptance of the Terms of Use.