NDLI: Watershed and Random Walks based depth estimation for semi-automatic 2D to 3D image conversion

Content Provider	IEEE Xplore Digital Library
Author	Xuyuan Xu Lai-Man Po Kwok-Wai Cheung Ka-Ho Ng Ka-Man Wong Chi-Wang Ting
Copyright Year	2012
Description	Author affiliation: Department of Computer Science, Chu Hai College of Higher Education, Hong Kong SAR, China (Kwok-Wai Cheung) \|\| Department of Electronic Engineering, City University of Hong Kong, China (Xuyuan Xu; Lai-Man Po; Ka-Ho Ng; Ka-Man Wong; Chi-Wang Ting)
Abstract	Depth map estimation from a single image is the key problem for the 2D to 3D image conversion. Many 2D to 3D converting processes, either automatic or semi-automatic, are proposed before. Quality of the depth map from automatic methods is low and there exists wrong depth values due to errors estimation in depth cue extraction. The semi-automatic approaches can generate a better quality of depth map based on the user-defined labels, which indicate a rough estimation of depth values in the scene, to generate the rest of depth value and reconstruct the stereoscopic image. However, they require complexity system and are very computational intensive. A simplified approach is to combine the depth maps from Graph Cuts and Random Walks to persevering the sharp boundary and fine detail inside the objects. The drawback is the time consuming of the energy minimization in the Graph Cuts. In this paper, a fast Watershed segmentation based on the priority queue, which indicates the neighbor distance relationship, is used to replace the Graph Cuts to generate the hard constraints depth map. It is appended to the neighbor cost in the Random Walks to generate the final depth map with hard constraints in the objects boundaries regions and fine detail inside objects. The Watershed and Random Walks are low computational intensive and can achieve approximate real time estimation which results in a fast stereoscopic conversion process. Experimental results demonstrate that it can produce good quality stereoscopic image in very short time.
Starting Page	84
Ending Page	87
File Size	1353426
Page Count	4
File Format	PDF
ISBN	9781467321921
e-ISBN	9781467321938
DOI	10.1109/ICSPCC.2012.6335592
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-08-12
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image segmentation Image color analysis Depth map estimation Stereo image processing Semi-automatic 2D to 3D Estimation Minimization 2D to 3D Floods Videos
Content Type	Text
Resource Type	Article

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