Research on the Technology of Gun Detection System for Android APP Videos Based on Deep Learning

doi:10.3969/j.issn.1671-1122.2016.09.030

Abstract

Abstract:

With the rapid development of the Moblile Internet, Android OS has become the most important internet content delivery channels. Unfortunately, different types of videos, which threaten the stability of the society, appear, due to chaotic APP supervision approaches. In this paper, with the objectives of monitoring the Android video applications automatically and thus purifying the network environment, we proposed a gun detection system, which is based on deep learning, for Android APP videos. By overcoming the difficulty of extracting the APP video data from the bottom layer of the Android system, we designed a new video acquiring approach according to the Android multimedia framework. We also developed a part-whole-gun (PWG) detection method based on the Faster R-CNN framework for object detection. Experimental results demonstrate decent performances for practical test images.

Key words: Android, video data capturing, deep learning, gun detection

CLC Number:

TP309

Qing LEI, Lihua JING, Deming ZHAO, Jilong ZHENG. Research on the Technology of Gun Detection System for Android APP Videos Based on Deep Learning[J]. Netinfo Security, 2016, 16(9): 149-153.

Figures/Tables 6

References 11

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