3D non-rigid registration using color: Color Coherent Point Drift

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Title: 3D non-rigid registration using color: Color Coherent Point Drift
Authors: Saval-Calvo, Marcelo | Azorin-Lopez, Jorge | Fuster-Guilló, Andrés | Villena Martínez, Víctor | Fisher, Robert B.
Research Group/s: Informática Industrial y Redes de Computadores
Center, Department or Service: Universidad de Alicante. Departamento de Tecnología Informática y Computación
Keywords: 3D non-rigid registration | 3D deformable registration | CCPD
Knowledge Area: Arquitectura y Tecnología de Computadores
Issue Date: 31-Jan-2018
Publisher: Elsevier
Citation: Computer Vision and Image Understanding. 2018. doi:10.1016/j.cviu.2018.01.008
Abstract: Research into object deformations using computer vision techniques has been under intense study in recent years. A widely used technique is 3D non-rigid registration to estimate the transformation between two instances of a deforming structure. Despite many previous developments on this topic, it remains a challenging problem. In this paper we propose a novel approach to non-rigid registration combining two data spaces in order to robustly calculate the correspondences and transformation between two data sets. In particular, we use point color as well as 3D location as these are the common outputs of RGB-D cameras. We have propose the Color Coherent Point Drift (CCPD) algorithm (an extension of the CPD method (Myronenko and Song, 2010)). Evaluation is performed using synthetic and real data. The synthetic data includes easy shapes that allow evaluation of the effect of noise, outliers and missing data. Moreover, an evaluation of realistic figures obtained using Blensor is carried out. Real data acquired using a general purpose Primesense Carmine sensor is used to validate the CCPD for real shapes. For all tests, the proposed method is compared to the original CPD showing better results in registration accuracy in most cases.
Sponsor: Authors acknowledge the projects from University of Alicante (Gre16-28) and Spanish Ministry (TIN2017-89069-R) supported with Feder funds.
URI: http://hdl.handle.net/10045/73437
ISSN: 1077-3142 (Print) | 1090-235X (Online)
DOI: 10.1016/j.cviu.2018.01.008
Language: eng
Type: info:eu-repo/semantics/article
Rights: © 2018 Elsevier Inc.
Peer Review: si
Publisher version: http://dx.doi.org/10.1016/j.cviu.2018.01.008
Appears in Collections:INV - I2RC - Artículos de Revistas

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