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Authors: Saddam Abdulwahab 1 ; Hatem Rashwan 1 ; Julian Cristiano 1 ; Sylvie Chambon 2 and Domenec Puig 1

Affiliations: 1 Department of Computer Engineering and Mathematics, Rovira i Virgili University, Tarragona and Spain ; 2 Department of Computing, IRIT, Université de Toulouse, Toulouse and France

ISBN: 978-989-758-354-4

Keyword(s): 2D/3D Registration, Support Vector Machine, Cross Domain, Depth Images, Curvilinear Saliency.

Related Ontology Subjects/Areas/Topics: Computer Vision, Visualization and Computer Graphics ; Features Extraction ; Image and Video Analysis ; Image Registration ; Shape Representation and Matching

Abstract: Registering a single intensity image to a 3D geometric model represented by a set of depth images is still a challenge. Since depth images represent only the shape of the objects, in turn, the intensity image is relative to viewpoint, texture and lighting condition. Thus, it is essential to firstly bring 2D and 3D representations to common features and then match them to find the correct view. In this paper, we used the concept of curvilinear saliency, related to curvature estimation, for extracting the shape information of both modalities. However, matching the features extracted from an intensity image to thousand(s) of depth images rendered from a 3D model is an exhausting process. Consequently, we propose to cluster the depth images into groups based on Clustering Rule-based Algorithm (CRA). In order to reduce the matching space between the intensity and depth images, a 2D/3D registration framework based on multi-class Support Vector Machine (SVM) is then used. SVM predicts the cl osest class (i.e., a set of depth images) to the input image. Finally, the closest view is refined and verified by using RANSAC. The effectiveness of the proposed registration approach has been evaluated by using the public PASCAL3D+ dataset. The obtaining results show that the proposed algorithm provides a high precision with an average of 88%. (More)

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Paper citation in several formats:
Abdulwahab, S.; Rashwan, H.; Cristiano, J.; Chambon, S. and Puig, D. (2019). Effective 2D/3D Registration using Curvilinear Saliency Features and Multi-Class SVM.In Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5 VISAPP: VISAPP, ISBN 978-989-758-354-4, pages 354-361. DOI: 10.5220/0007362603540361

@conference{visapp19,
author={Saddam Abdulwahab. and Hatem A. Rashwan. and Julian Cristiano. and Sylvie Chambon. and Domenec Puig.},
title={Effective 2D/3D Registration using Curvilinear Saliency Features and Multi-Class SVM},
booktitle={Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5 VISAPP: VISAPP,},
year={2019},
pages={354-361},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007362603540361},
isbn={978-989-758-354-4},
}

TY - CONF

JO - Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5 VISAPP: VISAPP,
TI - Effective 2D/3D Registration using Curvilinear Saliency Features and Multi-Class SVM
SN - 978-989-758-354-4
AU - Abdulwahab, S.
AU - Rashwan, H.
AU - Cristiano, J.
AU - Chambon, S.
AU - Puig, D.
PY - 2019
SP - 354
EP - 361
DO - 10.5220/0007362603540361

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