Yanushkevich, SvetlanaLai, Kenneth2015-05-012016-01-072015-05-012015Lai, K. (2015). Facial Biometrics using RGB-Depth Data (Master's thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca. doi:10.11575/PRISM/26140http://hdl.handle.net/11023/2229This thesis focuses on facial biometrics, acquired using multi-spectral sensors, such as RGB, depth, and infrared. This data is used for authorizing users of automated and semi-automated access systems, as well as for accumulating additional information regarding facial biometrics. In this work we show that depth data, taken using an inexpensive RGB-D sensor, helps find the head pose of a subject and extract frontal-view frames. We prove experimentally that usage of the frontal-view frames improves the efficiency of face recognition. Additionally, corresponding synchronized infrared video frames allow for more efficient temperature estimation from the frontal-views. Furthermore, this thesis describes potential applications of this approach in biometric-based security systems, as well as in biomedical and health care solutions. This also shows the promising future of using biometrics in natural and contactless control interfaces.engUniversity of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.Engineering--Electronics and ElectricalBiometricsFace recognitionRGB-Depthmaster thesishttp://dx.doi.org/10.11575/PRISM/26140