Name
Abstract | ||
|---|---|---|
We present a novel method to robustly and efficiently detect moving object, even under the complexity background, such as illumination changes, long shadows etc. This work is distinguished by three key contributions. The first is the integration of the Local Binary Pattern texture measure which extends the moving object detection work for light illumination changing. The second is the introduction of HSI color space measure which removes shadows for the background subtraction. The third contribution is a novel fuzzy way using the Choquet integral which improves detection accuracy. The experiment results using several dataset videos show the robustness and effectiveness of the proposed method. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.2298/CSIS1001201D | COMPUTER SCIENCE AND INFORMATION SYSTEMS |
Keywords | Field | DocType |
moving object detection,Local Binary Pattern,HSI,Choquet integral | Background subtraction,Object detection,Computer vision,Viola–Jones object detection framework,Color space,Computer science,Fuzzy logic,Local binary patterns,Robustness (computer science),Artificial intelligence,Choquet integral,Machine learning | Journal |
Volume | Issue | ISSN |
7 | 1 | 1820-0214 |
Citations | PageRank | References |
3 | 0.41 | 21 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ying Ding | 1 | 3 | 0.75 |
| Wenhui Li | 2 | 83 | 28.12 |
| Jingtao Fan | 3 | 8 | 3.53 |
| Huamin Yang | 4 | 19 | 17.29 |