Paper Info
Title
Robust transgender face recognition: Approach based on appearance and therapy factors
Abstract
Transgender face recognition is gaining increasing attention in the face recognition community because of its potential in real life applications. Despite extensive progress in traditional face recognition domain, it is very challenging to recognize faces under transgender setting. The gender transformation results in significant face variations, both in shape and texture gradually over time. This introduces additional complexities to existing face recognition algorithms to achieve a reliable performance. In this paper, we present a novel framework that incorporates appearance factor and a transformation factor caused due to Hormone Replacement Therapy (HRT) for recognition. To this extent, we employ the Hidden Factor Analysis (HFA) to jointly model a face under therapy as a linear combination of appearance and transformation factors. This is based on the intuition that the appearance factor captures the features that are unaffected by the therapy and transformation factor captures the feature changes due to therapy. Extensive experiments carried out on publicly available HRT transgender face database shows the efficacy of the proposed scheme with a recognition accuracy of 82.36%.
Year
DOI
Venue
2016
10.1109/ISBA.2016.7477226
2016 IEEE International Conference on Identity, Security and Behavior Analysis (ISBA)
Keywords
Field
DocType
robust transgender face recognition,therapy factors,appearance factor,gender transformation factor,hormone replacement therapy,hidden factor analysis,HRT transgender face database
Facial recognition system,Transgender,Three-dimensional face recognition,Psychology,Intuition,Feature extraction,Speech recognition,Robustness (computer science),Medical treatment,Face detection
Conference
Citations 
PageRank 
References 
1
0.36
8
Authors
4
Name
Order
Citations
PageRank
Vijay Kumar1363.83
R. G. Raghavendra2224.29
anoop m namboodiri3698.71
Christoph Busch416333.54