Name
Abstract | ||
|---|---|---|
This work presents a vision-based vehicle identification system which consists of object extraction, object tracking, occlusion detection and segmentation, and vehicle classification. Since the vehicles on the freeway may occlude each other, their trajectories may merge or split. To separate the occluded objects, we develop three processed: occlusion detection, motion vector calibration, and motion field clustering. Finally, the segmented objects are classified into seven different categorized vehicles. |
Year | DOI | Venue |
|---|---|---|
2004 | 10.1109/ICPR.2004.1333778 | ICPR (4) |
Keywords | Field | DocType |
occlusion detection,motion vector calibration,object extraction,pattern clustering,occluded object,traffic engineering computing,vision-based vehicle identification system,image segmentation,computer graphics,feature extraction,image classification,segmented object,motion field clustering,object tracking,object detection,computer vision,vehicle classification,occlusion segmentation,image motion analysis | Object detection,Computer vision,Motion field,Pattern recognition,Computer science,Segmentation,Image segmentation,Video tracking,Artificial intelligence,Cluster analysis,Contextual image classification,Motion vector | Conference |
Volume | ISSN | ISBN |
4 | 1051-4651 | 0-7695-2128-2 |
Citations | PageRank | References |
24 | 0.96 | 4 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chung-Lin Huang | 1 | 540 | 37.61 |
| Wen-Chieh Liao | 2 | 24 | 0.96 |