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A Synthetic Feature Skull Descriptor for 3D Skull Similarity Measurement
Joint Authors
Source
Mathematical Problems in Engineering
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-11-30
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
3D skull similarity measurement is a challenging and meaningful task in the fields of archaeology, forensic science, and anthropology.
However, it is difficult to correctly and directly measure the similarity between 3D skulls which are geometric models with multiple border holes and complex topologies.
In this paper, based on the synthetic feature method, we propose a novel 3D skull descriptor, synthetic wave kernel distance distribution (SWKDD) constructed by the laplace–beltrami operator.
By defining SWKDD, we obtain a concise global skull representation method and transform the complex 3D skull similarity measurement into a simple 1D vector similarity measurement.
First, we give the definition and calculation of SWKDD and analyse its properties.
Second, we represent a framework for 3D skull similarity measurement using the SWKDD of 3D skulls and details of the calculation steps involved.
Finally, we validate the effectiveness of our proposed method by calculating the similarity measurement of 3D skulls based on the real craniofacial database.
American Psychological Association (APA)
Zhang, Dan& Wang, Kang. 2019. A Synthetic Feature Skull Descriptor for 3D Skull Similarity Measurement. Mathematical Problems in Engineering،Vol. 2019, no. 2019, pp.1-12.
https://search.emarefa.net/detail/BIM-1197340
Modern Language Association (MLA)
Zhang, Dan& Wang, Kang. A Synthetic Feature Skull Descriptor for 3D Skull Similarity Measurement. Mathematical Problems in Engineering No. 2019 (2019), pp.1-12.
https://search.emarefa.net/detail/BIM-1197340
American Medical Association (AMA)
Zhang, Dan& Wang, Kang. A Synthetic Feature Skull Descriptor for 3D Skull Similarity Measurement. Mathematical Problems in Engineering. 2019. Vol. 2019, no. 2019, pp.1-12.
https://search.emarefa.net/detail/BIM-1197340
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1197340