Name
Abstract | ||
|---|---|---|
Robustness is an important factor for background modelling on various scenarios. Current pixel-based adaptive segmentation method cannot effectively tackle diverse objects simultaneously. To address this problem, in this study, a background modelling method using discriminative motion representation is proposed. Instead of simple usage of intensity to construct the background model, the proposed m... |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1049/iet-cvi.2016.0426 | IET Computer Vision |
Keywords | Field | DocType |
image motion analysis,image representation | False detection,Computer vision,Classification rule,Pattern recognition,Segmentation,Foreground detection,Robustness (computer science),Pixel,Artificial intelligence,Discriminative model,Mathematics | Journal |
Volume | Issue | ISSN |
11 | 6 | 1751-9632 |
Citations | PageRank | References |
2 | 0.35 | 38 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhong Zuofeng | 1 | 62 | 4.56 |
| Yong Xu | 2 | 339 | 31.64 |
| Li Zuoyong | 3 | 62 | 5.02 |
| Zhao Yinnan | 4 | 2 | 0.35 |