Extracting Iso-Disparity Strip Width using a Statistical Model in a Stereo Vision System

Abstract

Disparity map images, as outputs of a stereo vision system, are known as an effective approach in applications that need depth information in their procedure. One example of such applications is extracting planes with arbitrary attributes from a scene using the concept of iso-disparity strips. The width and direction of strips depend on the plane direction and position in the 3D space. In this paper, a statistical analysis is performed to model the behavior of these strips. This statistical analysis as well as a frequency analysis reveal that for each group of iso-disparity strips, which are corresponding to a single plane in 3D, the width of strips can be represented by an average value superposed by an Additive Gaussian Noise (AGN). This means that a simple averaging technique can significantly reduce the measurement noise in applications such as ground detection using these strips. Results show that the width of iso-disparity strips can be measured with an average precision of 96% using the presented noise model.