Authors
K.T. Nguyen, Florent Retraint, Cathel Zitzmann,
Title
Face recognition by thermal video using 3D information and vesselness features
In
2017 IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2017
Pages
68–73
Publisher
Institute of Electrical and Electronics Engineers Inc.
Year
2018
Publisher's URL
http://dx.doi.org/10.1109/ISSPIT.2017.8388321
Indexed by
Abstract
This paper aims to introduce a new approach for face recognition in thermal imagery by exploiting the depth information hidden in infrared video. The process starts by reconstructing a 3D model of the head from this video which contains frames in different poses to provide a depth image. On the other hand, the original thermal images which describe the intensity information can be enhanced and be transformed to a vascular network which is proven to be an efficient anatomical feature for face recognition. These two informations are regrouped to form an image where each pixel has two values, one for depth data and another for vessel intensity. This image goes through a hierarchical feature selection system using linear discriminant analysis and an Adaboost method learning to produce a feature template and to construct a final strong classifier. Numerical results on real date highlight the relevance of our proposed approach. © 2017 IEEE.
Affiliations
Offprint