Abstract
The detection of surrounding obstacle-free space is an essential task for many intelligent automotive and robotic applications. In this paper we present a method to detect obstacle-free pathways in real-time using depth maps from a pair of stereo images. Depth maps are obtained by processing the disparity between left and right images from a stereo-vision system. The proposed technique assumes that depth of pixels in obstacle-free pathways should increase slightly and linearly from the bottom of the image to the top. The proposed real-time detection checks whether the depth of groups of image columns matches a linear model. Only pixels fulfilling the matching requirements are identified as obstacle-free pathways. Experimental results with real outdoor stereo images show that the method performance is promising.
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