Augmented Reality with Multilayer Occlusion

Abstract

An algorithm for realizing multilayer occlusion in augmented reality (AR) is presented in this paper. We have designed a special scene graph tree comprised of some special nodes, namely EMO nodes. According to the location of real moving object, different EMO node will be activated in real-time, consequently realizing the multilayer occlusion. Differing qualitatively from previous work in AR occlusion, our algorithm realizes multilayer occlusion, and its application domain involves indoor-field occluded objects, which are several meters distant from the viewer. Previous related work has focused on monolayer occlusion, and near-field occluded objects, which are within or just beyond arm s reach. In addition, BP neural network is improved to correct the nonlinear error of magnetic sensor, consequently to detect occlusion more effectively. Experimental results are provided to demonstrate the multilayer indoor-field occlusion.