Computer vision methods for cranial sex estimation

The objective of this study is to demonstrate through empirical evaluation the potential of a number of computer vision (CV) methods for sex determination from human skull. To achieve this, six local feature representations, two feature learnings, and three classification algorithms are rigorously c...

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Bibliographic Details
Published inIPSJ transactions on computer vision and applications Vol. 9; no. 1; pp. 1 - 15
Main Authors Arigbabu, Olasimbo Ayodeji, Liao, Iman Yi, Abdullah, Nurliza, Mohamad Noor, Mohamad Helmee
Format Journal Article
LanguageEnglish
Published Berlin/Heidelberg Springer Berlin Heidelberg 29.09.2017
Springer Nature B.V
Subjects
Algorithms
Artificial Intelligence
Computer Imaging
Computer Science
Computer vision
Evaluation
Image Processing and Computer Vision
Pattern Recognition and Graphics
Research Paper
Robotics and Automation
Sex
User Interfaces and Human Computer Interaction
Vision
Forensic anthropology
Support vector machine
Multi-kernel learning
Sex determination
Kernel principal component analysis
Local feature representation
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Summary:The objective of this study is to demonstrate through empirical evaluation the potential of a number of computer vision (CV) methods for sex determination from human skull. To achieve this, six local feature representations, two feature learnings, and three classification algorithms are rigorously combined and evaluated on skull regions derived from skull partitions. Furthermore, we introduce for the first time the application of multi-kernel learning (MKL) on multiple features for sex prediction from human skull. In comparison to the classical forensic methods, the results in this study are competitive, attesting to the suitability of CV methods for sex estimation. The proposed approach is fully automatic.
ISSN:1882-6695
1882-6695
DOI:10.1186/s41074-017-0031-6