Differential and Statistical Approach to Partial Model Matching

Differential and Statistical Approach to Partial Model Matching

Partial model matching approaches are important to target recognition. In this paper, aiming at a 3D model, a novel solution utilizing Gaussian curvature and mean curvature to represent the inherent structure of a spatial shape is proposed. Firstly, a Point-Pair Set is constructed by means of filtra...

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Main Authors: Kehua Guo, Yongling Liu, Guihua Duan
Format: Article
Language:English
Published: Hindawi Limited 2013-01-01
Series:Mathematical Problems in Engineering
Online Access:http://dx.doi.org/10.1155/2013/249847
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spelling doaj-fd17156c0b2841399f5eac8466e030e62020-11-25T00:21:47ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472013-01-01201310.1155/2013/249847249847Differential and Statistical Approach to Partial Model MatchingKehua Guo0Yongling Liu1Guihua Duan2School of Information Science and Engineering, Central South University, Changsha 410083, ChinaSchool of Information Science and Engineering, Central South University, Changsha 410083, ChinaSchool of Information Science and Engineering, Central South University, Changsha 410083, ChinaPartial model matching approaches are important to target recognition. In this paper, aiming at a 3D model, a novel solution utilizing Gaussian curvature and mean curvature to represent the inherent structure of a spatial shape is proposed. Firstly, a Point-Pair Set is constructed by means of filtrating points with a similar inherent characteristic in the partial surface. Secondly, a Triangle-Pair Set is demonstrated after locating the spatial model by asymmetry triangle skeleton. Finally, after searching similar triangles in a Point-Pair Set, optimal transformation is obtained by computing the scoring function in a Triangle-Pair Set, and optimal matching is determined. Experiments show that this algorithm is suitable for partial model matching. Encouraging matching efficiency, speed, and running time complexity to irregular models are indicated in the study.http://dx.doi.org/10.1155/2013/249847
collection DOAJ
language English
format Article
sources DOAJ
author Kehua Guo
Yongling Liu
Guihua Duan
spellingShingle Kehua Guo
Yongling Liu
Guihua Duan
Differential and Statistical Approach to Partial Model Matching
Mathematical Problems in Engineering
author_facet Kehua Guo
Yongling Liu
Guihua Duan
author_sort Kehua Guo
title Differential and Statistical Approach to Partial Model Matching
title_short Differential and Statistical Approach to Partial Model Matching
title_full Differential and Statistical Approach to Partial Model Matching
title_fullStr Differential and Statistical Approach to Partial Model Matching
title_full_unstemmed Differential and Statistical Approach to Partial Model Matching
title_sort differential and statistical approach to partial model matching
publisher Hindawi Limited
series Mathematical Problems in Engineering
issn 1024-123X
1563-5147
publishDate 2013-01-01
description Partial model matching approaches are important to target recognition. In this paper, aiming at a 3D model, a novel solution utilizing Gaussian curvature and mean curvature to represent the inherent structure of a spatial shape is proposed. Firstly, a Point-Pair Set is constructed by means of filtrating points with a similar inherent characteristic in the partial surface. Secondly, a Triangle-Pair Set is demonstrated after locating the spatial model by asymmetry triangle skeleton. Finally, after searching similar triangles in a Point-Pair Set, optimal transformation is obtained by computing the scoring function in a Triangle-Pair Set, and optimal matching is determined. Experiments show that this algorithm is suitable for partial model matching. Encouraging matching efficiency, speed, and running time complexity to irregular models are indicated in the study.
url http://dx.doi.org/10.1155/2013/249847
work_keys_str_mv AT kehuaguo differentialandstatisticalapproachtopartialmodelmatching
AT yonglingliu differentialandstatisticalapproachtopartialmodelmatching
AT guihuaduan differentialandstatisticalapproachtopartialmodelmatching
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