Name
Title | ||
|---|---|---|
Video-Based Traffic Analysis System Using a Hierarchical Feature Point Grouping Approach |
Abstract | ||
|---|---|---|
This study presents a video-based car detection and tracking algorithm for traffic analysis system. By setting a detection window at the entry of a traffic lane, the algorithm applies a two-layer SVM classifier to detect car-passing events at the detection window. When car-passing event occurs, Harris corners are detected at the detection window and then tracked by optical flow. These tracked corners are then organized by using a hierarchical feature point grouping approach which not only groups the corners which should belong to a single vehicle but also rejects outlier corners. Each vehicle is thus detected and tracked. A variety of traffic parameters such as vehicle count, traffic flow density, vehicle speed detection, and lane change event detection can be further obtained. Experimental results reveal that the proposed method shows better performance than conventional background-subtraction based or virtual-wires based methods on challenging videos such as with traffic jam or at night. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/RVSP.2011.53 | RVSP |
Keywords | Field | DocType |
traffic lane,hierarchical feature point grouping,traffic jam,two-layer svm classifier,video signal processing,video-based car tracking algorithm,vehicle speed detection,harris corner detection,traffic engineering computing,traffic parameter,traffic analysis,video-based traffic analysis system,vehicle count,detection and tracking,feature extraction,image classification,support vector machine,traffic flow density,object tracking,image sequences,lane change event detection,video-based car detection,virtual-wires based method,object detection,car-passing event,traffic analysis system,detection window,feature point grouping,optical flow,hierarchical feature point grouping approach,video-based car detection algorithm,background-subtraction method,support vector machines,video surveillance,tracking,traffic flow,background subtraction,radar tracking | Object detection,Computer vision,Traffic analysis,Traffic flow,Pattern recognition,Corner detection,Computer science,Support vector machine,Feature extraction,Video tracking,Artificial intelligence,Optical flow | Conference |
ISBN | Citations | PageRank |
978-1-4577-1881-6 | 0 | 0.34 |
References | Authors | |
6 | 1 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chung-Hsien Huang | 1 | 39 | 7.92 |