Zou Beiji;Mohammed, Nurudeen;Zhu Chengzhang;Zhao Rongchang
INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS,2017年10(1):962-969 ISSN：1875-6891
[Mohammed, Nurudeen; Zhao Rongchang; Zou Beiji] Cent S Univ, Sch Informat Sci & Engn, South Lushan Rd, Changsha 410083, Hunan, Peoples R China.;[Zhu Chengzhang] Cent S Univ, Coll Literature & Journalism, South Lushan Rd, Changsha 410083, Hunan, Peoples R China.
[Zhu, CZ] Cent S Univ, Coll Literature & Journalism, South Lushan Rd, Changsha 410083, Hunan, Peoples R China.
Video Event Detection;Neuro-Fuzzy Inference;Crime Mapping;Hotspot Analysis
This paper presents a new approach to crime hotspot detection and monitoring. The approach consists of three phases' namely: video analysis, crime prediction and crime mapping. In video analysis, crime indicator events are modelled using statistical distribution of semantic concepts. In crime prediction, a neuro-fuzzy method is used to model indicator events. In crime mapping, kernel density estimation is used to detect crime hotspots. This approach is tested in a simulated platform using violent scene detection (VSD) 2014 dataset.