Crowd abnormal behavior detection based on motion similar entropy
It is an important research content of graphic processing in the field of intelligent video surveillance to detect abnormal events.An algorithm based on entropy of motion similarity (EMS) to detect abnormal behavior was proposed.Based on the optical flow algorithm,taking the bottom flow block as the...
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| Format: | Article |
| Language: | zho |
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Beijing Xintong Media Co., Ltd
2017-05-01
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| Series: | Dianxin kexue |
| Subjects: | |
| Online Access: | http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000−0801.2017117/ |
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| _version_ | 1841530123501699072 |
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| author | Fei LI Ken CHEN Meng LI Chunmei GUO |
| author_facet | Fei LI Ken CHEN Meng LI Chunmei GUO |
| author_sort | Fei LI |
| collection | DOAJ |
| description | It is an important research content of graphic processing in the field of intelligent video surveillance to detect abnormal events.An algorithm based on entropy of motion similarity (EMS) to detect abnormal behavior was proposed.Based on the optical flow algorithm,taking the bottom flow block as the basic unit to get the scene motion information,according to the concept of social network model,the construction scene of the motion network model (MNM) was proposed,the division of the scene particles motion similarity was completed,and the distribution EMS of MNM was calculated in the time domain.Finally,the obtained image entropy was compared with the reasonable threshold,to determine whether abnormal behavior occured.Experimental results indicate that the proposed algo-rithm can detect abnormal behavior effectively and show promising performance while comparing with the state of the art methods. |
| format | Article |
| id | doaj-art-420af2cfdfb044deba25d1dfb7fdfc81 |
| institution | Kabale University |
| issn | 1000-0801 |
| language | zho |
| publishDate | 2017-05-01 |
| publisher | Beijing Xintong Media Co., Ltd |
| record_format | Article |
| series | Dianxin kexue |
| spelling | doaj-art-420af2cfdfb044deba25d1dfb7fdfc812025-01-15T03:12:54ZzhoBeijing Xintong Media Co., LtdDianxin kexue1000-08012017-05-0133909859602368Crowd abnormal behavior detection based on motion similar entropyFei LIKen CHENMeng LIChunmei GUOIt is an important research content of graphic processing in the field of intelligent video surveillance to detect abnormal events.An algorithm based on entropy of motion similarity (EMS) to detect abnormal behavior was proposed.Based on the optical flow algorithm,taking the bottom flow block as the basic unit to get the scene motion information,according to the concept of social network model,the construction scene of the motion network model (MNM) was proposed,the division of the scene particles motion similarity was completed,and the distribution EMS of MNM was calculated in the time domain.Finally,the obtained image entropy was compared with the reasonable threshold,to determine whether abnormal behavior occured.Experimental results indicate that the proposed algo-rithm can detect abnormal behavior effectively and show promising performance while comparing with the state of the art methods.http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000−0801.2017117/crowd abnormal detectionentropy of motion similaritymotion network modelimage entropyoptical flow method |
| spellingShingle | Fei LI Ken CHEN Meng LI Chunmei GUO Crowd abnormal behavior detection based on motion similar entropy Dianxin kexue crowd abnormal detection entropy of motion similarity motion network model image entropy optical flow method |
| title | Crowd abnormal behavior detection based on motion similar entropy |
| title_full | Crowd abnormal behavior detection based on motion similar entropy |
| title_fullStr | Crowd abnormal behavior detection based on motion similar entropy |
| title_full_unstemmed | Crowd abnormal behavior detection based on motion similar entropy |
| title_short | Crowd abnormal behavior detection based on motion similar entropy |
| title_sort | crowd abnormal behavior detection based on motion similar entropy |
| topic | crowd abnormal detection entropy of motion similarity motion network model image entropy optical flow method |
| url | http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000−0801.2017117/ |
| work_keys_str_mv | AT feili crowdabnormalbehaviordetectionbasedonmotionsimilarentropy AT kenchen crowdabnormalbehaviordetectionbasedonmotionsimilarentropy AT mengli crowdabnormalbehaviordetectionbasedonmotionsimilarentropy AT chunmeiguo crowdabnormalbehaviordetectionbasedonmotionsimilarentropy |