Name
Abstract | ||
|---|---|---|
Wide Area Motion Imagery (WAMI) enables the surveillance of tens of square kilometers with one airborne sensor Each image can contain thousands of moving objects. Applications such as driver behavior analysis or traffic monitoring require precise multiple object tracking that is dependent on initial detections. However, low object resolution, dense traffic, and imprecise image alignment lead to split, merged, and missing detections. No systematic evaluation of moving object detection exists so far although many approaches have been presented in the literature. This paper provides a detailed overview of existing methods for moving object detection in WAMI data. Also we propose a novel combination of short-term background subtraction and suppression of image alignment errors by pixel neighborhood consideration. In total, eleven methods are systematically evaluated using more than 160,000 ground truth detections of the WPAFB 2009 dataset. Best performance with respect to precision and recall is achieved by the proposed one. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/WACV.2016.7477573 | 2016 IEEE Winter Conference on Applications of Computer Vision (WACV) |
Keywords | Field | DocType |
moving object detection,wide area motion imagery,WAMI data,airborne sensor,driver behavior analysis,traffic monitoring,multiple object tracking,image alignment errors,pixel neighborhood consideration,WPAFB 2009 dataset | Background subtraction,Object detection,Computer vision,Pattern recognition,Object-class detection,Computer science,Precision and recall,Video tracking,Ground truth,Pixel,Artificial intelligence,Image resolution | Conference |
ISSN | Citations | PageRank |
2472-6737 | 4 | 0.40 |
References | Authors | |
21 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lars Wilko Sommer | 1 | 31 | 9.49 |
| Michael Teutsch | 2 | 44 | 5.01 |
| Tobias Schuchert | 3 | 93 | 12.21 |
| Jürgen Beyerer | 4 | 315 | 75.37 |