Integration of multiple soft biometrics for human identification

Olasimbo Ayodeji Arigbabu, Sharifah Mumtazah Syed Ahmad, Wan Azizun Wan Adnan, Salman Yussof

Research output: Contribution to journalArticle

16 Citations (Scopus)

Abstract

We propose a computational approach to human identification based on the integration of face and body related soft biometric traits. In previous studies on soft biometrics, several methods for human identification using semantic descriptions have been introduced. Though the results attained exhibit the effectiveness of such techniques in image retrieval and short term tracking of subjects, semantics literally limits the ability of a biometric system to provide conclusive identification. This paper presents a new framework for biometric identification based solely on multiple measured soft biometric traits. The paper describes techniques for extracting/estimating face and body based soft biometric traits from frame set. Furthermore, we utilized a sequential attribute combination method to perform attribute selection prior to integration at match score level. Finally, an evaluation of five score fusion techniques is performed. The results show that the proposed framework can be utilized to model an adequate soft biometric system with rank-1 identification rate of 88%.

Original languageEnglish
Pages (from-to)278-287
Number of pages10
JournalPattern Recognition Letters
Volume68
DOIs
Publication statusPublished - 15 Dec 2015

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All Science Journal Classification (ASJC) codes

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence

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