loading
Documentation
  • Login
  • Sign-Up

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Manal H. Alassaf 1 ; Yeny Yim 2 and James K. Hahn 3

Affiliations: 1 George Washington University and Taif University, United States ; 2 Samsung Electronics, Korea, Republic of ; 3 George Washington University, United States

ISBN: 978-989-758-003-1

Keyword(s): Non-rigid Registration, Iterative Closest Point Algorithm, ICP, Cover Tree, Clustering, Nearest Neighbor Search.

Related Ontology Subjects/Areas/Topics: Applications ; Applications and Services ; Computer Vision, Visualization and Computer Graphics ; Geometry and Modeling ; Image and Video Analysis ; Image Registration ; Image-Based Modeling ; Medical Image Applications ; Pattern Recognition ; Segmentation and Grouping ; Shape Representation and Matching ; Software Engineering

Abstract: We propose a novel non-rigid registration method that computes the correspondences of two deformable surfaces using the cover tree. The aim is to find the correct correspondences without landmark selection and to reduce the computational complexity. The source surface S is initially aligned to the target surface T to generate a cover tree from the densely distributed surface points. The cover tree is constructed by taking into account the positions and normal vectors of the points and used for hierarchical clustering and nearest neighbor search. The cover tree based clustering divides the two surfaces into several clusters based on the geometric features, and each cluster on the source surface is transformed to its corresponding cluster on the target. The nearest neighbor search from the cover tree reduces the search space for correspondence computation, and the source surface is deformed to the target by optimizing the point pairs. The correct correspondence of a given source point i s determined by choosing one target point with the best correspondence measure from the k nearest neighbors. The proposed energy function with Jacobian penalty allows deforming the surface accurately and with less deformation folding. (More)

PDF ImageFull Text

Download
Sign In Guest: Register as new SCITEPRESS user or Join INSTICC now for free.

Sign In SCITEPRESS user: please login.

Sign In INSTICC Members: please login. If not a member yet, Join INSTICC now for free.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 54.144.50.90. INSTICC members have higher download limits (free membership now)

In the current month:
Recent papers: 1 available of 1 total
2+ years older papers: 2 available of 2 total

Paper citation in several formats:
H. Alassaf M., Yim Y. and K. Hahn J. (2014). Non-rigid Surface Registration using Cover Tree based Clustering and Nearest Neighbor Search.In Proceedings of the 9th International Conference on Computer Vision Theory and Applications (VISIGRAPP 2014)ISBN 978-989-758-003-1, pages 579-587. DOI: 10.5220/0004738405790587

@conference{visapp14,
author={Manal H. Alassaf and Yeny Yim and James K. Hahn},
title={Non-rigid Surface Registration using Cover Tree based Clustering and Nearest Neighbor Search},
booktitle={Proceedings of the 9th International Conference on Computer Vision Theory and Applications (VISIGRAPP 2014)},
year={2014},
pages={579-587},
doi={10.5220/0004738405790587},
isbn={978-989-758-003-1},
}

TY - CONF

JO - Proceedings of the 9th International Conference on Computer Vision Theory and Applications (VISIGRAPP 2014)
TI - Non-rigid Surface Registration using Cover Tree based Clustering and Nearest Neighbor Search
SN - 978-989-758-003-1
AU - H. Alassaf M.
AU - Yim Y.
AU - K. Hahn J.
PY - 2014
SP - 579
EP - 587
DO - 10.5220/0004738405790587

Sorted by: Show papers

Note: The preferred Subjects/Areas/Topics, listed below for each paper, are those that match the selected paper topics and their ontology superclasses.
More...

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.

Show authors

Note: The preferred Subjects/Areas/Topics, listed below for each author, are those that more frequently used in the author's papers.
More...