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A remote facial expression recognition surveillance system utilizing PCA and KNN algorithms within an Internet of Vehicles architecture can stably and accurately identify driver states such as road rage, fatigue, and drunk driving. Novelty: ClaimNovelty.METHODOLOGICAL. Consensus alignment: ConsensusAlignment.NEUTRAL.

September 1, 2015

Design and Implementation of Remote Facial Expression Recognition Surveillance System Based on PCA and KNN Algorithms

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Abstract

Internet of Vehicles is new concept proposed in recently year extended from Internet of Things. It plays an important role in improving traffic situation. This system is respected as a part of Internet of Vehicles aimed to identify road rage, fatigue driving or drunk driving and so on by recognizing drivers' facial expression. With Internet of Things architecture, this system has a multi-function system module. By combining AJAX with SSH2 framework, the web service of this system is established. PCA and KNN are the core algorithm of facial expression recognition and the related parameters is optimized. According to the topological graph of the system network, this system has been deployed in a certain vehicle network company and it performed stable, efficient and accurate.

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