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3D shape restoration using sparse representation and separation of illumination effects

Lookup NU author(s): Dr Wai Lok Woo, Professor Satnam Dlay


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This paper investigates the problem of extracting 3D shape from flat 2D images. In contrast with conventional methods, this work uses two images captured from the same position but under different illuminations to reconstruct a 3D shape. The proposed novel algorithm is based on an underdetermined system by seeking sparseness and statistical independence between direct illumination and object shape within a statistical estimation framework. The technology proposed surpasses the minimum requirement of the photometric method, which needs at least three input images. In addition, a new statistical model was developed which is updated by the Expectation-Maximization algorithm to accommodate the system noise appearing on the images. The performance of the proposed algorithm significantly increased the accuracy over conventional methods whilst reducing the computational complexity. (C) 2013 Elsevier B.V. All rights reserved.

Publication metadata

Author(s): Woo WL, Dlay SS

Publication type: Article

Publication status: Published

Journal: Signal Processing

Year: 2014

Volume: 103

Pages: 258-272

Print publication date: 01/10/2014

ISSN (print): 0165-1684

ISSN (electronic): 1879-2677

Publisher: Elsevier


DOI: 10.1016/j.sigpro.2013.12.006


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