Proceedings ArticleDOI
Evolutionary granular approach for recognizing faces altered due to plastic surgery
Himanshu Bhatt,Samarth Bharadwaj,Richa Singh,Mayank Vatsa,Afzel Noore +4 more
- pp 720-725
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TLDR
An evolutionary granular approach for matching face images that have been altered by plastic surgery procedures is proposed using genetic algorithm to simultaneously optimize the selection of feature extractor for each face granule along with finding optimal weights corresponding to each facegranule for matching.Abstract:
Recognizing faces with altered appearances is a challenging task and is only now beginning to be addressed by researchers. The paper presents an evolutionary granular approach for matching face images that have been altered by plastic surgery procedures. The algorithm extracts discriminating information from non-disjoint face granules obtained at different levels of granularity. At the first level of granularity, both pre and post-surgery face images are processed by Gaussian and Laplacian operators to obtain face granules at varying resolutions. The second level of granularity divides face image into horizontal and vertical face granules of varying size and information content. At the third level of granularity, face image is tessellated into non-overlapping local facial regions. An evolutionary approach is proposed using genetic algorithm to simultaneously optimize the selection of feature extractor for each face granule along with finding optimal weights corresponding to each face granule for matching. Experiments on pre and post-plastic surgery face images show that the proposed algorithm provides at least 15% better identification performance as compared to other face recognition algorithms.read more
Citations
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Proceedings ArticleDOI
Can facial cosmetics affect the matching accuracy of face recognition systems
TL;DR: The impact of a commonly used face altering technique that has received limited attention in the biometric literature, viz., non-permanent facial makeup is studied and it is suggested that this simple alteration can indeed compromise the accuracy of a biometric system.
Book ChapterDOI
On the Effects of Image Alterations on Face Recognition Accuracy
TL;DR: This chapter analyzes the effects of intentional or unintentional face image alterations on face recognition algorithms and the human capabilities to deal with altered images in scenarios where the user template is created from printed photographs rather than from images acquired live during enrollment.
Proceedings ArticleDOI
Mitigating effects of plastic surgery: Fusing face and ocular biometrics
Raghavender Jillela,Arun Ross +1 more
TL;DR: A fusion approach is proposed that combines information from the face and ocular regions to enhance recognition performance in the identification mode, and provides the highest reported recognition performance on a publicly accessible plastic surgery database.
Journal ArticleDOI
Deceiving faces: When plastic surgery challenges face recognition
TL;DR: A survey of the state of the art on face recognition, starting by an analysis of the diffusion of the facial plastic surgery and describing the key aspects of each of the most statistically relevant treatments available, resumed by a synthetic table.
Book ChapterDOI
Face recognition after plastic surgery: a comprehensive study
Xin Liu,Shiguang Shan,Xilin Chen +2 more
TL;DR: An ensemble of Gabor Patch classifiers via Rank-Order list Fusion (GPROF) is proposed, inspired by the assumption of the interior consistency of face components in terms of identity, to address FRAPS problem.
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Journal ArticleDOI
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