Abstract
The accuracy of automated human face recognition algorithms can significantly degrade while recognizing same subjects under make-up and disguised appearances. Increasing constraints on enhanced security and surveillance requires enhanced accuracy from face recognition algorithms for faces under disguise and/or makeup. This paper presents a new database for face images under disguised and make-up appearances the development of face recognition algorithms under such covariates. This database has 2460 images from 410 different subjects and is acquired under real environment, focuses on make-up and disguises covariates and also provides ground truth (eye glass, goggle, mustache, beard) for every image. This can enable developed algorithms to automatically quantify their capability for identifying such important disguise attribute during the face recognition We also present comparative experimental results from two popular commercial matchers and from recent publications. Our experimental results suggest significant performance degradation in the capability of these matchers in automatically recognizing these faces. We also analyze face detection accuracy from these matchers. The experimental results underline the challenges in recognizing faces under these covariates. Availability of this new database in public domain will help to advance much needed research and development in recognizing make-up and disguised faces.
Original language | English |
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Title of host publication | ISBA 2016 - IEEE International Conference on Identity, Security and Behavior Analysis |
Publisher | IEEE |
ISBN (Electronic) | 9781467397278 |
DOIs | |
Publication status | Published - 23 May 2016 |
Event | 2nd IEEE International Conference on Identity, Security and Behavior Analysis, ISBA 2016 - Sakura Hall, Tohoku University, Sendai, Japan Duration: 29 Feb 2016 → 2 Mar 2016 |
Conference
Conference | 2nd IEEE International Conference on Identity, Security and Behavior Analysis, ISBA 2016 |
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Country/Territory | Japan |
City | Sendai |
Period | 29/02/16 → 2/03/16 |
ASJC Scopus subject areas
- Computer Vision and Pattern Recognition
- Human Factors and Ergonomics