Smoothing algorithm for 3-D surface rendering from stereo images

Abstract

Methods for determining the three-dimensional (3-D) form of complex objects in a scene from a pair of images using the principles of stereo vision are described. A pair of stereo images are epipolar- or raster-scan-aligned to restrict the search to one dimension along the horizontal lines as a first step in location of image feature points. A correlation window of size 5/spl times/5 around a pixel on the left image is superimposed on a similar window centered around every pixel along the same scan line of the right image. A normalized cross-correlation value for every pair of windows is determined. The image points in the right image which give the maximum correlation value are chosen as the corresponding points for the associated points in the left image. Once the corresponding points are found, the disparity is determined. This initial disparity map is noisy. A smoothing or interpolation algorithm has been developed, greatly increasing the number of feature points that can be identified. Sobel Edge detection is employed to locate discontinuities. Disparity values at edge points are added back into the smoothed disparity map, and the modified smoothed disparity map is used for 3-D rendering.