Person-Of-Interest Detection System Using Cloud-Supported Computerized-Eyewear

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“Person-Of-Interest Detection System Using Cloud-Supported Computerized-Eyewear” by Xi Wang, Xi Zhao, Varun Prakash, Zhimin Gao, Tao Feng, Omprakash Gnawali, and Weidong Shi. In Proceedings of the IEEE International Conference on Technologies for Homeland Security (IEEE HST 2013), November 2013.

Abstract

Detecting Person-Of-Interest (POI), e.g., fugitives, criminals and terrorists in public spaces is a critical requirement of many law enforcers and police officers. In realty, most law enforcement personnel cannot effectively differentiate POIs from millions of faces and thus demand a portable assistant to recognize faces, in order to take the golden opportunity taking the POIs into immediate custody. Unfortunately, current face recognition systems are stationary and limited to a small scale of POI datasets. In this paper, we investigate a wearable computerized-eyewear based face recognition system. This system is a portable device which can accompany a police officer during patrolling or other tasks. The eyewear is connected to a cloud based face recognition system via wireless networks. Facial images captured by the mounted camera are sent to the cloud for identity retrieval. When the system finds a POI, it would alert officers via overlaying a virtual identity tag on the real POI's face on the transparent screen of the eyewear. We provide approaches to greatly minimize recognition time, including leveraging the large storage and high computational capacities provided by the cloud. The cloud enables nationwide POI database and supports parallel computing for face recognition.

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BibTeX entry:

@inproceedings{poidetect-hst2013,
   author = {Xi Wang and Xi Zhao and Varun Prakash and Zhimin Gao and Tao
	Feng and Omprakash Gnawali and Weidong Shi},
   title = {{Person-Of-Interest Detection System Using Cloud-Supported
	Computerized-Eyewear}},
   booktitle = { Proceedings of the IEEE International Conference on
	Technologies for Homeland Security (IEEE HST 2013)},
   month = { November },
   year = {2013}
}