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Please use this identifier to cite or link to this item: https://dspace.lboro.ac.uk/2134/20253

Title: Using retinex for point selection in 3D shape registration
Authors: Liu, Yonghuai
Martin, Ralph R.
De Dominicis, Luigi
Li, Baihua
Issue Date: 2014
Publisher: © Elsevier
Citation: LIU, Y. ... et al, 2014. Using retinex for point selection in 3D shape registration. Pattern Recognition, 47 (6), pp.2126-2142
Abstract: Inspired by retinex theory, we propose a novel method for selecting key points from a depth map of a 3D freeform shape; we also use these key points as a basis for shape registration. To find key points, first, depths are transformed using the Hotelling method and normalized to reduce their dependence on a particular viewpoint. Adaptive smoothing is then applied using weights which decrease with spatial gradient and local inhomogeneity; this preserves local features such as edges and corners while ensuring smoothed depths are not reduced. Key points are those with locally maximal depths, faithfully capturing shape. We show how such key points can be used in an efficient registration process, using two state-of-the-art iterative closest point variants. A comparative study with leading alternatives, using real range images, shows that our approach provides informative, expressive, and repeatable points leading to the most accurate registration results. © 2014 Elsevier Ltd.
Version: Accepted for publication
DOI: 10.1016/j.patcog.2013.12.015
URI: https://dspace.lboro.ac.uk/2134/20253
Publisher Link: http://dx.doi.org/10.1016/j.patcog.2013.12.015
ISSN: 0031-3203
Appears in Collections:Published Articles (Computer Science)

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