Stereo Vision System with the Grouping Process of Multiple Reaction-Diffusion Models

Abstract

The present paper proposes a system that detects a stereo disparity map from random-dot stereograms with the grouping process. A simple operation for random-dot stereograms converts the stereo correspondence problem to the segmentation one. For solving the segmentation problem derived from random-dot stereograms, the stereo vision system proposed here utilizes the grouping process of our previously proposed model. The model for the grouping process consists of multiple reaction-diffusion models, each of which governs segments having a disparity in the stereo vision system. A self-inhibition mechanism due to strong inhibitory diffusion within a particular reaction-diffusion model and a mutual-inhibition mechanism among the models are built in the proposed system. Experimental results for artificially generated random-dot stereograms show the validity of the proposed system.