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      지능형 영상 감시 시스템에서 사람 자세 추정을 이용한 납치 상황 인식 = A Kidnapping Detection Using Human Pose Estimation in Intelligent Video Surveillance Systems

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      https://www.riss.kr/link?id=A105545052

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      다국어 초록 (Multilingual Abstract)

      In this paper, a kidnapping detection scheme in which human pose estimation is used to classify accurately between kidnapping cases and normal ones is proposed. To estimate human poses from input video, human’s 10 joint information is extracted by O...

      In this paper, a kidnapping detection scheme in which human pose estimation is used to classify accurately between kidnapping cases and normal ones is proposed. To estimate human poses from input video, human’s 10 joint information is extracted by OpenPose library. In addition to the features which are used in the previous study to represent the size change rates and the regularities of human activities, the human pose estimation features which are computed from the location of detected human’s joints are used as the features to distinguish kidnapping situations from the normal accompanying ones. A frame-based kidnapping detection scheme is generated according to the selection of J48 decision tree model from the comparison of several representative classification models. When a video has more frames of kidnapping situation than the threshold ratio after two people meet in the video, the proposed scheme detects and notifies the occurrence of kidnapping event. To check the feasibility of the proposed scheme, the detection accuracy of our newly proposed scheme is compared with that of the previous scheme. According to the experiment results, the proposed scheme could detect kidnapping situations more 4.73% correctly than the previous scheme.

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      목차 (Table of Contents)

      • Abstract
      • Ⅰ. Introduction
      • Ⅱ. Related works
      • Ⅲ. A kidnapping detection using human pose estimation
      • Ⅳ. Experiment and evaluation
      • Abstract
      • Ⅰ. Introduction
      • Ⅱ. Related works
      • Ⅲ. A kidnapping detection using human pose estimation
      • Ⅳ. Experiment and evaluation
      • Ⅳ. Conclusions
      • REFERENCES
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      참고문헌 (Reference)

      1 Hall. Mark A, "The WEKA data mining software: An Update" 11 (11): 10-18, 2009

      2 Marti A. Hearst, "Support vector machines" 13 (13): 18-28, 1998

      3 "Statistics Korea"

      4 Zhe. Cao, "Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields" 7291-7299, 2017

      5 "OpenPose library"

      6 Kevin P. Murphy, "Naive Bayes classifiers, Vol. 18" 2006

      7 Soumi. Paul, "Microsoft Kinect in Gesture Recognition: A Short Review" 8 (8): 2071-2076, 2015

      8 Powers, "Evaluation: from precision, recall and F-measure to ROC, informedness, markedness and correlation" 2 (2): 37-63, 2011

      9 YTN News, "Detect immediately dangerous situations ... prevent crime with intelligent cctv"

      10 Neeraj. Bhargava, "Decision Tree Analysis on J48 Algorithm for Data Mining" 3 (3): 1114-1119, 2013

      1 Hall. Mark A, "The WEKA data mining software: An Update" 11 (11): 10-18, 2009

      2 Marti A. Hearst, "Support vector machines" 13 (13): 18-28, 1998

      3 "Statistics Korea"

      4 Zhe. Cao, "Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields" 7291-7299, 2017

      5 "OpenPose library"

      6 Kevin P. Murphy, "Naive Bayes classifiers, Vol. 18" 2006

      7 Soumi. Paul, "Microsoft Kinect in Gesture Recognition: A Short Review" 8 (8): 2071-2076, 2015

      8 Powers, "Evaluation: from precision, recall and F-measure to ROC, informedness, markedness and correlation" 2 (2): 37-63, 2011

      9 YTN News, "Detect immediately dangerous situations ... prevent crime with intelligent cctv"

      10 Neeraj. Bhargava, "Decision Tree Analysis on J48 Algorithm for Data Mining" 3 (3): 1114-1119, 2013

      11 Hall. Mark A, "Correlation-based feature selection for machine learning" University of Waikato 1999

      12 Shih-En. Wei, "Convolutional pose machines" 4724-4732, 2016

      13 정충식, "CCTV 통합관제센터의 운영 개선 방안에 관한 연구: 부산시 통합관제센터를 중심으로" 한국지역정보화학회 18 (18): 123-154, 2015

      14 Lei Xu, "Best first strategy for feature selection" 706-708, 1988

      15 Divya. J, "Automatic Video Based Surveillance System for Abnormal Behavior Detection" 4 (4): 1743-1747, 2013

      16 Ji-Hyen. Choi, "A Prediction Method for Abnormal Behavior based on Omni-view Pattern" 401-403, 2015

      17 Ryu-Hyeok. Gwon, "A Kidnapping Detection Scheme Using Frame-Based Classification for Intelligent Video Surveillance" 345-354, 2013

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      학술지 이력

      학술지 이력
      연월일 이력구분 이력상세 등재구분
      2026 평가예정 재인증평가 신청대상 (재인증)
      2020-01-01 평가 등재학술지 유지 (재인증) KCI등재
      2017-01-01 평가 등재학술지 유지 (계속평가) KCI등재
      2013-01-01 평가 등재학술지 유지 (등재유지) KCI등재
      2010-01-01 평가 등재학술지 유지 (등재유지) KCI등재
      2007-01-01 평가 등재학술지 선정 (등재후보2차) KCI등재
      2006-01-01 평가 등재후보 1차 PASS (등재후보1차) KCI등재후보
      2004-07-01 평가 등재후보학술지 선정 (신규평가) KCI등재후보
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      학술지 인용정보

      학술지 인용정보
      기준연도 WOS-KCI 통합IF(2년) KCIF(2년) KCIF(3년)
      2016 0.44 0.44 0.44
      KCIF(4년) KCIF(5년) 중심성지수(3년) 즉시성지수
      0.43 0.38 0.58 0.15
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