Journal
IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY
Volume 8, Issue 1, Pages 239-253Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TIFS.2012.2226580
Keywords
Active shapemodel; component-based face representation; face recognition; feature extraction
Funding
- World Class University (WCU) program through the National Research Foundation of Korea
- Ministry of Education, Science and Technology [R31-2008-000-10008-0]
- National Research Foundation of Korea [R31-2012-000-10008-0] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
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This paper presents a framework for component-based face alignment and representation that demonstrates improvements in matching performance over the more common holistic approach to face alignment and representation. This work is motivated by recent evidence from the cognitive science community demonstrating the efficacy of component-based facial representations. The component-based framework presented in this paper consists of the following major steps: 1) landmark extraction using Active Shape Models (ASM), 2) alignment and cropping of components using Procrustes Analysis, 3) representation of components with Multiscale Local Binary Patterns (MLBP), 4) per-component measurement of facial similarity, and 5) fusion of per-component similarities. We demonstrate on three public datasets and an operational dataset consisting of face images of 8000 subjects, that the proposed component-based representation provides higher recognition accuracies over holistic-based representations. Additionally, we show that the proposed component-based representations: 1) are more robust to changes in facial pose, and 2) improve recognition accuracy on occluded face images in forensic scenarios.
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