LVT Face Database: A Benchmark Database for Visible and Hidden Face Biometrics.

Although the estimation of eHealth parameters from face visuals (images and videos) has grown as a major area of research in the past years, deep-learning-based models are still challenged by RGB lack of robustness, for instance with changing illumination conditions. As a means to overcome these limitations and to unlock new opportunities, thermal imagery has arisen as a favorable alternative to solidify different technologies such as heart rate estimation from faces. However, the reduced number of databases containing thermal imagery and the lack of health annotation of the subjects in them limits the exploration of this spectrum. Motivated by this, in this paper, we present our Label-EURECOM Visible and Thermal (LVT) Face Database for face biometrics. This database is the first that contains paired visible and thermal images and videos from 52 subjects with metadata of 22 soft biometrics and health parameters. Moreover, we establish the first study introducing the potential of thermal images for weight estimation from faces on our database.