A self-occlusion detection approach based on depth image using SVM

Abstract

This paper describes a novel self-occlusion detection approach for depth image using SVM. This work is distinguished by three contributions. The first contribution is the introduction of a new self-occlusion detection idea, which takes the self-occlusion as a classification problem for the first time, thus the accuracy of the detection result is improved. The second contribution is two new self-occlusion-related features, named maximal depth difference and included angle. The third contribution is a specific self-occlusion detection algorithm. Experimental results not only show that the proposed approach is feasible and effective, but also show that our works produce better results than those previously published. © 2012 Zhang and Liu; licensee InTech.