Yanushkevich, SvetlanaLu, Kok Yee2016-08-252016-08-2520162016http://hdl.handle.net/11023/3219This study introduces a wearable facial recognition system for face blindness, or prosopagnosia, rehabilitation. Prosopagnosia is the inability to recognize familiar faces, which affects 2.5% of the world population (148 million people). The design and implementation of a facial recognition system tailored to patients with prosopagnosia is a priority in the field of clinical neuroscience. The goal of this study is to demonstrate the feasibility of implementing a wearable stand-alone (not connected to a PC or a smartphone) system-on-chip (SoC) that performs facial recognition and could be used to assist individuals affected by prosopagnosia. This system is designed as an autonomous embedded platform built on eyewear with SoC and a custom designed circuit board. The implementation is based on the open source computer vision image processing algorithms embedded within a compact-scale processor. The advantages of the device are its lightness, compactness, single independent image processing capability and long operational time. The system performs real-time facial recognition and informs the user of the results by displaying the name of the recognized person.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 ElectricalBiometricProsopagnisiamaster thesis10.11575/PRISM/25570