Citation: | CAI Yiheng, LIU Tianhao, LIU Jiaqi, GUO Yajun, HU Shaobin. Research on Crowd Video Anomaly Detection Algorithm Based on Dual-branch[J]. Journal of Electronics & Information Technology, 2022, 44(7): 2496-2503. doi: 10.11999/JEIT210341 |
[1] |
LIU Wen, LUO Weixin, LIAN Dongze, et al. Future frame prediction for anomaly detection-A new baseline[C]. 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, Salt Lake City, USA, 2018: 6536–6545.
|
[2] |
LI Yuanyuan, CAI Yiheng, LIU Jiaqi, et al. Spatio-temporal unity networking for video anomaly detection[J]. IEEE Access, 2019, 7: 172425–172432. doi: 10.1109/ACCESS.2019.2954540
|
[3] |
ZHOU Bolei, TANG Xiaoou, ZHANG Hepeng, et al. Measuring crowd collectiveness[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2014, 36(8): 1586–1599. doi: 10.1109/TPAMI.2014.2300484
|
[4] |
DIREKOGLU C, SAH M, and O’CONNOR N E. Abnormal crowd behavior detection using novel optical flow-based features[C]. The 14th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS), Lecce, Italia, 2017: 1–6.
|
[5] |
蒋俊, 张卓君, 高明亮, 等. 一种基于脉线流卷积神经网络的人群异常行为检测算法[J]. 工程科学与技术, 2020, 52(6): 215–222.
JIANG Jun, ZHANG Zhuojun, GAO Mingliang, et al. An abnormal crowd behavior detection method based on streak flow CNN[J]. Advanced Engineering Sciences, 2020, 52(6): 215–222.
|
[6] |
王洪雁, 周梦星. 基于光流及轨迹的人群异常行为检测[J]. 吉林大学学报: 工学版, 2020, 50(6): 2229–2237.
WANG Hongyan and ZHOU Mengxing. Crowd abnormal behavior detection based on optical flow and track[J]. Journal of Jilin University:Engineering and Technology Edition, 2020, 50(6): 2229–2237.
|
[7] |
XIE Shaoci, ZHANG Xiaohong, and CAI Jing. Video crowd detection and abnormal behavior model detection based on machine learning method[J]. Neural Computing and Applications, 2019, 31(1): 175–184.
|
[8] |
MEHRAN R, OYAMA A, and SHAH M. Abnormal crowd behavior detection using social force model[C]. 2009 IEEE Conference on Computer Vision and Pattern Recognition, Miami, USA, 2009: 935–942.
|
[9] |
周培培, 丁庆海, 罗海波, 等. 视频监控中的人群异常行为检测与定位[J]. 光学学报, 2018, 38(8): 97–105.
ZHOU Peipei, DING Qinghai, LUO Haibo, et al. Anomaly detection and location in crowded surveillance videos[J]. Acta Optica Sinica, 2018, 38(8): 97–105.
|
[10] |
CAI Yiheng, LIU Jiaqi, GUO Yajun, et al. Video anomaly detection with multi-scale feature and temporal information fusion[J]. Neurocomputing, 2021, 423: 264–273. doi: 10.1016/j.neucom.2020.10.044
|
[11] |
CONG Yang, YUAN Junsong, and LIU Ji. Abnormal event detection in crowded scenes using sparse representation[J]. Pattern Recognition, 2013, 46(7): 1851–1864. doi: 10.1016/j.patcog.2012.11.021
|
[12] |
WU Shandong, MOORE B E, and SHAH M. Chaotic invariants of Lagrangian particle trajectories for anomaly detection in crowded scenes[C]. Proceedings of 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, San Francisco, USA, 2010: 2054–2060.
|
[13] |
SALIGRAMA V and CHEN Zhu. Video anomaly detection based on local statistical aggregates[C]. Proceedings of 2012 IEEE Conference on Computer Vision and Pattern Recognition, Providence, USA, 2012: 2112–2119.
|
[14] |
ISOLA P, ZHU Junyan, ZHOU Tinghui, et al. Image-to-image translation with conditional adversarial networks[C]. Proceedings of 2017 IEEE Conference on Computer Vision and Pattern Recognition, Honolulu, USA, 2017: 1125–1134.
|
[15] |
XIONG Guogang, CHENG Jun, WU Xinyu, et al. An energy model approach to people counting for abnormal crowd behavior detection[J]. Neurocomputing, 2012, 83: 121–135. doi: 10.1016/j.neucom.2011.12.007
|
[16] |
彭月平, 蒋镕圻, 徐蕾. 基于C3D-GRNN模型的人群异常行为识别算法[J]. 测控技术, 2020, 39(7): 44–50.
PENG Yueping, JIANG Rongqi, and XU Lei. An algorithm for identifying crowd abnormal behavior based on C3D-GRNN model[J]. Measurement &Control Technology, 2020, 39(7): 44–50.
|