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Ruben Vera-Rodriguez ; Pedro Tome ; Julian Fierrez ; Javier Ortega-Garcia, "Fusion of footsteps and face biometrics on an unsupervised and uncontrolled environment", Sensing Technologies for Global Health, Military Medicine, Disaster Response, and Environmental Monitoring II; and Biometric Technology for Human Identification IX, Proc. SPIE 8371 (May 1, 2012); doi:10.1117/12.918550. Copyright 2012 Society of Photo‑Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.Proceedings of the II Sensing Technologies for Global Health, Military Medicine, Disaster Response, and Environmental Monitoring; and IX Biometric Technology for Human Identification (Baltimore, Maryland, USA)This paper reports for the first time experiments on the fusion of footsteps and face on an unsupervised and not controlled environment for person authentication. Footstep recognition is a relatively new biometric based on signals extracted from people walking over floor sensors. The idea of the fusion between footsteps and face starts from the premise that in an area where footstep sensors are installed it is very simple to place a camera to capture also the face of the person that walks over the sensors. This setup may find application in scenarios like ambient assisted living, smart homes, eldercare, or security access. The paper reports a comparative assessment of both biometrics using the same database and experimental protocols. In the experimental work we considertwo different applications: smart homes (small group of users with a large set of training data) and security access (larger group of users with a small set of training data)  obtaining results of 0.9% and 5.8% EER respectively for the fusion of both modalities. This is a significant performance improvement compared with the results obtainedby the individual systems.This work has been partially supported by projects Contexts (S2009/TIC-1485), Bio-Challenge (TEC2009-11186) and ”Catedra UAM-Telefonica”