NDLI: SDG Cut: 3D Reconstruction of Non-lambertian Objects Using Graph Cuts on Surface Distance Grid

Content Provider	IEEE Xplore Digital Library
Author	Tianli Yu Ahuja, N. Wei-Chao Chen
Copyright Year	2006
Description	Author affiliation: Univ. of Illinois at Urbana-Champaign (Tianli Yu)
Abstract	We show that the approaches to 3D reconstruction that use volumetric graph cuts to minimize a cost function over the object surface have two types of biases, the minimal surface bias and the discretization bias. These biases make it difficult to recover surface extrusions and other details, especially when a non-lambertian photo-consistency measure is used. To reduce these biases, we propose a new iterative graph cuts based algorithm that operates on the Surface Distance Grid (SDG), which is a special discretization of the 3Dspace, constructed using a signed distance transform of the current surface estimate. It can be shown that SDG significantly reduces the minimal surface bias, and transforms the discretization bias into a controllable degree of surface smoothness. Experiments on 3D reconstruction of non-lambertian objects confirm the effectiveness of our algorithm over previous methods.
Starting Page	2269
Ending Page	2276
File Size	1927356
Page Count	8
File Format	PDF
ISBN	0769525970
ISSN	10636919
DOI	10.1109/CVPR.2006.267
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-06-17
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Surface reconstruction Cost function Image reconstruction Level set Minimization methods Rough surfaces Surface roughness Reconstruction algorithms Shape Photometry
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition Software

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