Smartphone-based fatigue detection system using progressive locating method


Smartphone applications became very widespread today as they supply useful functionalities to our daily lives over standard voice services. They provide a tiny but powerful computing platform where intelligent algorithms will be coded into some live-saving merchandise that profoundly impact our daily lifestyles. A mobile fatigue detection system that is proposed in this study is a crucial life-saving application running on smartphone. Mobile detection system faces technological challenges such as: (i) embracing relatively low-resolution images in image recognition; (ii) supporting fast response time given an occasional-power CPU as compared to a desktop laptop; and (iii) demanding for prime prediction accuracy by light-weight Machine Learning algorithms, as the software programs embedded in smartphones is resource constrained. Solutions with respect to indoor facial profiling system that are mainly based mostly on progressive locating methodology for eye detection are discussed during this study. Acceptable experimental results in terms of eye detection rate and driver fatigue detection in different situations are presented.

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