The 11th Iranian and the first International Conference on Machine Vision and Image Processing

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

Benyamin Kheradvar, Amir Mousavinia, Amir M. Sodagar
The 11th Iranian and the first International Conference on Machine Vision and Image Processing (MVIP 2020)

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.

Keywords: Iso-disparity Layers, Iso-disparity Strips, Noise Model, Plane Detection, Additive Gaussian Noise



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