Study on Intelligent Security Camera Systems for the Automated Detection of Nighttime Snatching Incidents using Deep Neural Networks
Itaru Nagayama, Akira Miyahara, Koichi Shimabukuro · IEEJ Transactions on Industry Applications · 2016
In this paper, we propose an intelligent security camera system for the automated detection of snatching incidents on streets during the night. Although over a half of all snatching incidents occur at night, this has not been considered in previous studies. Thus, an intelligent security camera system using a deep neural network and SAM (snatching action model) is presented in this paper, for the automated detection of snatching incidents at night. Certain characteristics of motion are determined from video streams, and using a deep neural network the system automatically classifies the situations in the video streams into criminal or non-criminal scenes. We consider many types of scenarios to perform experiments regarding snatching incidents on streets at night. The experimental results show that the system can effectively detect snatching incidents with an accuracy of 96.66%.