Research Topics



Obstacle Detection by In-vehicle Stereovision

descriptif

Many roads are not totaly planar and often present hills and valleys because of environment topography. Nevertheless, the majority of existing techniques for road obstacle detection assumes that the road is planar. This can cause several issues: imprecision as regards the real position of obstacles as well as false obstacle detection or obstacle detection failures. In order to increase the reliability of the obstacle detection process, "v-disparity" proposes an original, fast and robust method for detecting the obstacles without using the flat-earth geometry assumption; this method is able to cope with uphill and downhill gradients as well as dynamic pitching of the vehicle. Our approach is based on the construction and investigation of the "v-disparity" image which provides a good representation of the geometric content of the road scene. The advantage of this image is that it provides semi-global matching and is able to perform robust obstacle detection even in the case of partial occlusion. Furthermore, this detection is performed without any explicit extraction of coherent structures such as road edges or lane-markings in the stereo image pair.

Publications
  1. Charbonnier, P., Muzet, V., Nicolle, P., Hautière, N. a. J.-P. and Aubert, D. Stereovision applied to road scene analysis. In Bulletin des Laboratoires des Ponts et Chaussées, 272: 57-74, 2008.    
  2. Hautière, N., Tarel, J.-P. and Aubert, D. Simultaneous Contrast Restoration and Obstacles Detection: First Results. In IEEE Intelligent Vehicles Symposium (IV'07), Istanbul, Turkey, pages 130-135, 2007.    
  3. Hautière, N., Labayrade, R., Perrollaz, M. and Aubert, D. Road Scene Analysis by Stereovision: a Robust and Quasi-Dense Approach. In IEEE International Conference on Control Automation Robotics and Vision (ICARCV’06), Singapore, 2006.    
  4. Perrollaz, M., Labayrade, R., Royère, C. and Hautière, N. a. D. Long Range Obstacle Detection Using Laser Scanner And Stereovision. In IEEE Intelligent Vehicles Symposium (IV'06), Tokyo, Japan, pages 182-187, 2006.    

Slides

descriptifICARCV2006 presentation

Posters

descriptifIV2007 poster

Related topics

Autonomous systems
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