Name
Abstract | ||
|---|---|---|
The rapid development of Internet technology brings convenience to our life and also brings various hidden dangers. Violent video is one of the hidden dangers. Therefore, this paper proposes a P3D-LSTM recognition method based on multi-feature fusion for violent video recognition. In this paper, starting from video's static image, frame difference image and optical flow feature, the neural network for extracting corresponding features is constructed respectively, and then late fusion method is adopted to fuse the features or decision scores to obtain video classification labels. Finally, the experiment is carried out on two public databases and self-built violent database. As far as the recognition accuracy is concerned, this method has certain application prospect in classify violent video. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/ISCID.2018.00079 | 2018 11th International Symposium on Computational Intelligence and Design (ISCID) |
Keywords | Field | DocType |
deep learning,video recognition of violence,multi-feature fusion | Static image,Pattern recognition,Computer science,Frame difference,Artificial intelligence,Deep learning,Fuse (electrical),Artificial neural network,Optical flow,The Internet | Conference |
Volume | ISSN | ISBN |
01 | 2165-1701 | 978-1-5386-8527-3 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xingyu Xu | 1 | 3 | 2.41 |
| Xiaoyu Wu | 2 | 1 | 1.36 |
| Ge Wang | 3 | 532 | 71.66 |
| Huimin Wang | 4 | 0 | 0.34 |