This paper presents some techniques for synthesizing novel view for a virtual viewpoint from two given views cap-tured at different viewpoints to achieve both high quality and high efficiency. The whole process consis...This paper presents some techniques for synthesizing novel view for a virtual viewpoint from two given views cap-tured at different viewpoints to achieve both high quality and high efficiency. The whole process consists of three passes. The first pass recovers depth map. We formulate it as pixel labelling and propose a bisection approach to solve it. It is accomplished in log2n(n is the number of depth levels) steps,each of which involves a single graph cut computation. The second pass detects occluded pixels and reasons about their depth. It fits a foreground depth curve and a background depth curve using depth of nearby fore-ground and background pixels,and then distinguishes foreground and background pixels by minimizing a global energy,which involves only one graph cut computation. The third pass finds for each pixel in the novel view the corresponding pixels in the input views and computes its color. The whole process involves only a small number of graph cut computations,therefore it is efficient. And,visual artifacts in the synthesized view can be removed successfully by correcting depth of the occluded pixels. Experimental results demonstrate that both high quality and high efficiency are achieved by the proposed techniques.展开更多
基金Project (No. 2002CB312101) supported by the National Basic Re-search Program (973) of China
文摘This paper presents some techniques for synthesizing novel view for a virtual viewpoint from two given views cap-tured at different viewpoints to achieve both high quality and high efficiency. The whole process consists of three passes. The first pass recovers depth map. We formulate it as pixel labelling and propose a bisection approach to solve it. It is accomplished in log2n(n is the number of depth levels) steps,each of which involves a single graph cut computation. The second pass detects occluded pixels and reasons about their depth. It fits a foreground depth curve and a background depth curve using depth of nearby fore-ground and background pixels,and then distinguishes foreground and background pixels by minimizing a global energy,which involves only one graph cut computation. The third pass finds for each pixel in the novel view the corresponding pixels in the input views and computes its color. The whole process involves only a small number of graph cut computations,therefore it is efficient. And,visual artifacts in the synthesized view can be removed successfully by correcting depth of the occluded pixels. Experimental results demonstrate that both high quality and high efficiency are achieved by the proposed techniques.
