| Violence detection in surveillance video using low-level features | |
| Zhou, Peipei1,2,3,4; Ding, Qinghai1,5; Luo, Haibo1,3,4; Hou, Xinglin1,2,3,4 | |
| Corresponding Author | Zhou, Peipei(zhoupeipei@sia.cn) |
| 2018-10-03 | |
| Source Publication | PLOS ONE
 |
| ISSN | 1932-6203 |
| Volume | 13Issue:10Pages:15 |
| Abstract | It is very important to automatically detect violent behaviors in video surveillance scenarios, for instance, railway stations, gymnasiums and psychiatric centers. However, the previous detection methods usually extract descriptors around the spatiotemporal interesting points or extract statistic features in the motion regions, leading to limited abilities to effectively detect video-based violence activities. To address this issue, we propose a novel method to detect violence sequences. Firstly, the motion regions are segmented according to the distribution of optical flow fields. Secondly, in the motion regions, we propose to extract two kinds of low-level features to represent the appearance and dynamics for violent behaviors. The proposed low-level features are the Local Histogram of Oriented Gradient (LHOG) descriptor extracted from RGB images and the Local Histogram of Optical Flow (LHOF) descriptor extracted from optical flow images. Thirdly, the extracted features are coded using Bag of Words (BoW) model to eliminate redundant information and a specific-length vector is obtained for each video clip. At last, the video-level vectors are classified by Support Vector Machine (SVM). Experimental results on three challenging benchmark datasets demonstrate that the proposed detection approach is superior to the previous methods. |
| DOI | 10.1371/journal.pone.0203668 |
| Indexed By | SCI |
| Language | 英语 |
| WOS Research Area | Science & Technology - Other Topics |
| WOS Subject | Multidisciplinary Sciences |
| WOS ID | WOS:000446342400026 |
| Publisher | PUBLIC LIBRARY SCIENCE |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://ir.imr.ac.cn/handle/321006/129856 |
| Collection | 中国科学院金属研究所 |
| Corresponding Author | Zhou, Peipei |
| Affiliation | 1.Chinese Acad Sci, Shenyang Inst Automat, Shenyang, Liaoning, Peoples R China 2.Univ Chinese Acad Sci, Beijing, Peoples R China 3.Chinese Acad Sci, Key Lab Optoelect Informat Proc, Shenyang, Liaoning, Peoples R China 4.Key Lab Image Understanding & Comp Vis, Shenyang, Liaoning, Peoples R China 5.Space Star Technol Co Ltd, Beijing, Peoples R China |
| Recommended Citation GB/T 7714 | Zhou, Peipei,Ding, Qinghai,Luo, Haibo,et al. Violence detection in surveillance video using low-level features[J]. PLOS ONE,2018,13(10):15. |
| APA | Zhou, Peipei,Ding, Qinghai,Luo, Haibo,&Hou, Xinglin.(2018).Violence detection in surveillance video using low-level features.PLOS ONE,13(10),15. |
| MLA | Zhou, Peipei,et al."Violence detection in surveillance video using low-level features".PLOS ONE 13.10(2018):15. |
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