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Stereo Matching by Incorporating Depth Cues

MA Xiangyin1,2,ZHA Hongbin21.College of Computer Science and Technology,Zhejiang University of Technology,Hangzhou 310023;2.Key Laboratory on Machine Perception(Ministry of Education),Peking University,Beijing 100871  
Focusing on scenes of outdoor buildings,the authors present graph-based stereo matching methods that incorporate depth cues to acquire more accurate disparity maps.Firstly,given a portion of scan data,planar disparity layers,which correspond to 3D planes,are precisely extracted to compose the label set.After that,the graph-based matching algorithm can be formulated in the color segment domain instead of pixel domain.Furthermore,in order to avoid the inconvenient scanning for every scene,the scanner is only used to create a training set consisting of image-depthmap pairs.Then the depth cues,predicted through training a Markov Random Field to model the relationship between the depth and the image features,can still serve as extra constraint for the correspondence problem.The experimental results show the convincing performance of proposed methods in the reconstruction of different scenes.
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