Automatic 2D-to-3D Image Conversion based on Depth Map Estimation

Abstract

Recent advances in 3D have increased the importance of stereoscopic content creation and processing. Therefore, converting existing 2D contents into 3D contents is very important for growing 3D market. The most difficult task in 2D-to-3D conversion is estimating depth map from a single-view image. Thus, in this paper, we propose a novel algorithm to estimate the map by simulating haze as a global image feature. Besides, the visual artifacts of the synthesized left- and right-views can also be effectively eliminated by recovering the separation and loss of foreground objects in the proposed algorithm. Experimental results show that our algorithm can produce a good 3D stereoscopic effect and prevent the separation and loss artifacts with low computational complexity.