Distance recovery of 3D objects from stereo images using Hough transform

This paper examines recovering the depth of an object from two stereo images by correlating matching feature points. The principle concern of this paper is to demonstrate one method of feature point extraction. The orientation of the two viewers with respect to each other is fixed, this allows us to make use of the epipolar constraint for depth recovery. The methodology for extracting feature points from each image are: perform edge detection on each original image; use the Hough transform to identify the lines which define the image; label feature points as the intersections of lines where the intersection is a valid point in the edge detected image. The above method was very accurate with respect to recovering the depth of input images which were in certain orientations. However, the algorithm was too sensitive to error in the Hough transform space to allow for consistent evaluation of depth for all orientations.