Latest revision as of 19:56, 28 January 2021

Abstract

International audience; This paper deals with road plane detection by image analysis in the context of automatic driver assistance systems. In this context, free navigable space detection is a very important step for any navigation and obstacle detection system. We propose a low-level combination of two main visual processes: stereovision and motion. We define a common representation that allows simple projections of stereo information to easy-interpretable features in a motion space. We chose to combine two robust cumulative techniques: the stereo-based approach V-disparity and the motion-based approach C-velocity. The combination requires the definition of a common formalism. Results on synthetic image sequences and on KITTI database images reveal that our approach is more efficient than a higher level combination method. We show that it is possible, using no prior knowledge nor any calibration, to improve detection by a low cost method that exploits only image processing and a very simple stereo and motion combination.

Original document

The different versions of the original document can be found in:

• https://hal.archives-ouvertes.fr/hal-01319728

• http://xplorestaging.ieee.org/ielx7/7395988/7396880/07396921.pdf?arnumber=7396921,

http://dx.doi.org/10.1109/icves.2015.7396921

• https://hal.archives-ouvertes.fr/hal-01319728,

http://doi.org/10.1109/ICVES.2015.7396921,

http://ieeexplore.ieee.org/document/7396921,

https://doi.org/10.1109/ICVES.2015.7396921,

https://dblp.uni-trier.de/db/conf/icves/icves2015.html#DeghdacheB15,

https://academic.microsoft.com/#/detail/2288924862