Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group
  • Journal of the Optical Society of Korea
  • Vol. 20,
  • Issue 2,
  • pp. 239-244
  • (2016)

A Novel Approach to Mugshot Based Arbitrary View Face Recognition

Open Access Open Access

Abstract

Mugshot face images, routinely collected by police, usually contain both frontal and profile views. Existing automated face recognition methods exploited mugshot databases by enlarging the gallery with synthetic multi-view face images generated from the mugshot face images. This paper, instead, proposes to match the query arbitrary view face image directly to the enrolled frontal and profile face images. During matching, the 3D face shape model reconstructed from the mugshot face images is used to establish corresponding semantic parts between query and gallery face images, based on which comparison is done. The final recognition result is obtained by fusing the matching results with frontal and profile face images. Compared with previous methods, the proposed method better utilizes mugshot databases without using synthetic face images that may have artifacts. Its effectiveness has been demonstrated on the Color FERET and CMU PIE databases.

© 2016 Optical Society of Korea

PDF Article
More Like This
Image-based face recognition under illumination and pose variations

Shaohua Kevin Zhou and Rama Chellappa
J. Opt. Soc. Am. A 22(2) 217-229 (2005)

A de-illumination scheme for face recognition based on fast decomposition and detail feature fusion

Yi Zhou, Sheng-Tong Zhou, Zuo-Yang Zhong, and Hong-Guang Li
Opt. Express 21(9) 11294-11308 (2013)

Dictionaries for image and video-based face recognition [Invited]

Vishal M. Patel, Yi-Chen Chen, Rama Chellappa, and P. Jonathon Phillips
J. Opt. Soc. Am. A 31(5) 1090-1103 (2014)

Cited By

Optica participates in Crossref's Cited-By Linking service. Citing articles from Optica Publishing Group journals and other participating publishers are listed here.


Select as filters


Select Topics Cancel
© Copyright 2024 | Optica Publishing Group. All rights reserved, including rights for text and data mining and training of artificial technologies or similar technologies.