A Neuro-Fuzzy Crime Prediction Model Based on Video Analysis

作     者：ZOU Beiji Nurudeen Mohammed ZHU Chengzhang ZHANG Ziqian ZHAO Rongchang WANG Lei 

作者机构：School of Information Science and EngineeringCentral South University College of Literature and JournalismCentral South University 

出 版 物：《Chinese Journal of Electronics》 (电子学报(英文))

年 卷 期：2018年第27卷第5期

页      面：968-975页

核心收录：

学科分类：030605[法学-犯罪学] 03[法学] 0306[法学-公安学] 

基　　金：supported by the National Natural Science Foundation of China(No.61573380,No.61702559) the Fundamental Research Funds for the Central Universities of Central South University(No.2017zzts715,No.2017zzts723) 

主　　题：Hybrid intelligent systems(HIS) Subtractive clustering Video event detection Crime prediction 

摘      要：A hybrid neuro-fuzzy model for predicting crime in a wide area such as a town or district in *** model is built using what we describe as crime indicator events extracted from simulated wide area surveillance network. The framework principally involves two phases,namely video analysis and crime modeling phases. In video analysis a concept based approach for video event detection is used to detect crime indicator events. Based on the extracted indicators with other related variables, a fuzzy inference system capable of learning is constructed in the second phase. The model is constructed using Violent scene detection(VSD) 2014 dataset and testing is done using UCR-Videoweb dataset. The experimental results show that the proposed method is quite demonstrative and promising.