Electronics and Telecommunications Trends (전자통신동향분석)

Electronics and Telecommunications Research Institute (한국전자통신연구원)
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Trends in Dynamic Crime Prediction Technologies based on Intelligent CCTV

지능형 CCTV 기반 동적 범죄예측 기술 동향

  • 박상욱 (신인증.물리보안연구실) ;
  • 오선호 (신인증.물리보안연구실) ;
  • 박수완 (신인증.물리보안연구실) ;
  • 임경수 (신인증.물리보안연구실) ;
  • 최범석 (신인증.물리보안연구실) ;
  • 박소희 (신인증.물리보안연구실) ;
  • 김상원 (신인증.물리보안연구실) ;
  • 한승완 (신인증.물리보안연구실) ;
  • 한종욱 (신인증.물리보안연구실) ;
  • 김건우 (신인증.물리보안연구실)
  • Published : 2020.04.01
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Abstract

Predicting where and when a crime may occur in an area of interest is one of many strategies of predictive policing. Multidimensional analysis, including CCTV, can overcome the limitations of hotspot prediction, especially of violent crimes. In order to identify the precursors of a crime, it is necessary to analyze dynamic data such as attributes and activities of people, social information, environmental information, traffic flows, and weather. These parameters can be recognized by CCTV. In addition, it provides accurate analysis of the circumstances of a crime in a dynamic situation, calculates the risk, and predicts the probability of a crime occurring in the near future. Additionally, it provides ways to gather historical criminal datasets, including sensitive personal information.

Keywords

References

  1. K Aguirre et al., "Future crime: Assessing twenty first century crime prediction," STRATEGIC NOTE, 2019.
  2. Melanie-Angela Neuilly et al., "Predicting Recidivism in Homicide Offenders Using Classification Tree Analysis," Homicide Studies, 2011, pp. 165-176.
  3. 신민규 외, "5대 범죄와 물리적 환경 영향요인의 상관성 분석," 한국지도학회지, 2018, pp. 131-140.
  4. Ying-Lung Lin et al., "Grid-Based Crime Prediction Using Geographical Features," Int. J. Geo-Inf., 2018.
  5. 박우현 외, "범죄예방정책의 바람직한 추진방향," 경찰학논총, 2017, pp. 125-156. https://doi.org/10.16961/POLIPS.2020.15.1.125
  6. 김의명 외, "연속수치지도와 유동인구를 이용한 범죄취약 추정지역 추출," 한국지도학회지, 2019, pp. 59-68.
  7. 박진이 외, "격자망 분석을 통한 범죄 발생 취약 지역 추출 기법," 한국측량학회지, 2015, pp. 221-229.
  8. 류연수, "스마트치안 국내외 사례와 향후 과제," 행정포커스, 2017, pp. 16-21.
  9. Fieke Jansen, "Data Driven Policing in the Context of Europe, Data Justice Lab, 2018.
  10. Japan Times, "Kanagawa police to launch AI-based predictive policing system before Olympics," 2018년 1월 29일.
  11. 한국과학기술기획평가원, "안면인식 도입 확산과 국내 활성화 방안 모색," 과학기술&ICT 정책.기술 동향, 2019, pp. 1-17.
  12. 국토교통부, "전자발찌 범죄, 전국 CCTV로 잡는다," 2019년 3월 29일.
  13. 최종원 외, "행동 패턴 기반 범죄예측 모델 연구," 한국위성정보통신학회논문지, 2016, pp. 55-57.
  14. Mei Wang et al., "Deep Face Recognition," arXiv: 1804.06655, 2019.
  15. Bong-Nam Kang et al., "Hierarchical Feature-Pair Relation Networks for Face Recognition," CVPR Workshop, 2019.
  16. Xing Fan et al., "SphereReID: Deep Hypersphere Manifold Embedding for Person Re-Identication," arXiv: 1807.00537, 2018.
  17. Guangcong Wang et al., "Spatial-Temporal Person Reidentification," AAAI, 2019, arXiv: 1812.03282.
  18. S. M. Silva et al., "License Plate Detection and Recognition in Unconstrained Scenarios," ECCV, 2018.
  19. https://www.aicitychallenge.org/
  20. https://research.google.com/audioset/
  21. Waqas Sultani et al., "Real-world Anomaly Detection in Surveillance Videos," CVPR, 2018, arXiv: 1801.04264.
  22. Yi Zhu et al., "Motion-Aware Feature for Improved Video Anomaly Detection," BMVC, 2019, arXiv: 1907.10211.
  23. http://www.crimestats.or.kr/
  24. https://www.scourt.go.kr/
  25. FBI, "2019 National Incident-Based Reporting System (NIBRS) Technical Specification," https://www.fbi.gov/services/cjis/ucr
  26. 양형위원회, "2019 양형기준 추록(Sentencing Guidelines)," 2019.07.
  27. 대한의사협회, "진단서 등 작성.교부 지침(How to Write and Issue Medical Certificates)," 2015.03.
  28. 김성준, "한국에서 빅데이터를 활용한 범죄예방시스템 구축을 위한 연구," 한국인터넷방송통신학회 논문지, 2017, pp. 217-221.
  29. Karan Aggarwal et al., "Adversarial Unsupervised Representation Learning for Activity Time-Series," AAAI, 2019, arXiv:1811.06847.
  30. 보안뉴스, "다양해진 개인영상정보보호 기법, 어떤 게 있나," 2018년 7월 1일.
  31. Noah Johnson et al., "Towards Practical Differential Privacy for SQL Queries," VLDB, 2018, arXiv: 1706.09479.