Abstract
In this article a robust thermal face recognition methodology based on the use of local interest points and descriptors, is proposed. The methodology consists of the following stages: face segmentation, vascular network detection, wide baseline matching using local interest points and descriptors, and classification. The main contribution of this work is the use of a standard wide baseline matching methodology for the comparison of vascular networks from thermal face images. The proposed methodology is validated using a database of thermal images. This work could be of high interest for HRI applications related with the visual recognition of humans, as the ones included in the RoboCup @Home league, because the use of thermal images may overcome limitations such as dependency on illumination conditions and facial expressions.
This research was partially funded by FONDECYT under Project Number 1090250.
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Hermosilla, G., Loncomilla, P., Ruiz-del-Solar, J. (2011). Thermal Face Recognition Using Local Interest Points and Descriptors for HRI Applications. In: Ruiz-del-Solar, J., Chown, E., Plöger, P.G. (eds) RoboCup 2010: Robot Soccer World Cup XIV. RoboCup 2010. Lecture Notes in Computer Science(), vol 6556. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20217-9_3
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DOI: https://doi.org/10.1007/978-3-642-20217-9_3
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