Name
Abstract | ||
|---|---|---|
Personal videos often contain visual distractors, which are objects that are accidentally captured and can distract viewers from focusing on the main subjects. We propose a method to automatically detect and localize these distractors through learning from a manually labeled dataset. To achieve spatially and temporally coherent detection, we propose extracting features at the temporal-superpixel l... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/TMM.2018.2790163 | IEEE Transactions on Multimedia |
Keywords | Field | DocType |
Feature extraction,Visualization,Cameras,Streaming media,Multimedia communication,Computational modeling | Computer vision,Pattern recognition,Computer science,Convolutional neural network,Visualization,Support vector machine,Feature extraction,Artificial intelligence,Recall,Video quality | Journal |
Volume | Issue | ISSN |
20 | 8 | 1520-9210 |
Citations | PageRank | References |
3 | 0.38 | 0 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Fang-Lue Zhang | 1 | 269 | 15.60 |
| Xian Wu | 2 | 18 | 3.00 |
| Ruilong Li | 3 | 24 | 3.05 |
| Jue Wang | 4 | 2871 | 155.89 |
| Zhao-Heng Zheng | 5 | 3 | 0.38 |
| Shi-Min Hu | 6 | 3466 | 188.22 |