Name
Abstract | ||
|---|---|---|
Background modeling is a key step of background subtraction methods used in the context of static camera. The goal is to obtain a clean background and then detect moving objects by comparing it with the current frame. This paper describes a novel fuzzy approach, for moving object detection which is capable of processing images extremely rapidly and achieving high detection rates. This work integrates the Local Binary Pattern texture feature and HSI color feature by a novel fuzzy way using the Choquet integral, which extends the moving object detection work for light illumination changing and shadowing. The results of several dataset videos show the robustness and effectiveness of the proposed method. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/CADCG.2009.5246826 | 2009 11TH IEEE INTERNATIONAL CONFERENCE ON COMPUTER-AIDED DESIGN AND COMPUTER GRAPHICS, PROCEEDINGS |
Keywords | Field | DocType |
background subtraction,pixel,feature extraction,data mining,computational modeling,computer vision,local binary pattern,lighting,fuzzy set theory,choquet integral | Background subtraction,Computer vision,Object detection,Viola–Jones object detection framework,Pattern recognition,Computer science,Fuzzy logic,Local binary patterns,Feature extraction,Fuzzy set,Robustness (computer science),Artificial intelligence | Conference |
Volume | Issue | Citations |
null | null | 0 |
PageRank | References | Authors |
0.34 | 1 | 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 |