Name
Abstract | ||
|---|---|---|
A vision-based vehicle detection method is presented in this paper. The proposed method is composed of two steps, i.e., hypothesis generation and hypothesis verification. An adaptive background modeling and updating method is proposed to detect foreground regions in video sequences. With the prior knowledge of the vehicle appearance, the possible vehicle locations are extracted from the foreground regions and the touched vehicles are separated. Finally, hypothesized regions are verified by comparing their appearances with vehicle model. The performance of the proposed method is verified on videos captured under versatile conditions, and good results are achieved even in heavy traffic conditions. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/ICIP.2010.5653674 | ICIP |
Keywords | Field | DocType |
background estimation,vehicle detection,video sequences,traffic videos,hypothesis generation,traffic engineering computing,hypothesis verification,vision-based vehicle detection method,adaptive background updating,location extraction,feature extraction,automated highways,image sequences,adaptive background modeling,object detection,automatic vehicle detection,intelligent transportation system,video surveillance,lighting,pixel | Object detection,Computer vision,Pattern recognition,Computer science,Feature extraction,Vehicle detection,Artificial intelligence,Pixel,Intelligent transportation system,Hypothesis verification,Traffic conditions | Conference |
ISSN | ISBN | Citations |
1522-4880 E-ISBN : 978-1-4244-7993-1 | 978-1-4244-7993-1 | 0 |
PageRank | References | Authors |
0.34 | 2 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Qiong Cao | 1 | 0 | 0.68 |
| Rujie Liu | 2 | 147 | 15.49 |
| Fei Li | 3 | 23 | 4.62 |
| Yuehong Wang | 4 | 72 | 4.66 |