Name
Title | ||
|---|---|---|
A real-time approach for autonomous detection and tracking of moving objects from UAV |
Abstract | ||
|---|---|---|
A new approach to autonomously detect and track moving objects in a video captured by a moving camera from a UAV in real-time is proposed in this paper. The introduced approach replaces the need for a human operator to perform video analytics by autonomously detecting moving objects and clustering them for tracking purposes. The effectiveness of the introduced approach is tested on the footage taken from a real UAV and the evaluation results are demonstrated in this paper. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/EALS.2014.7009502 | Evolving and Autonomous Learning Systems |
Keywords | DocType | Citations |
autonomous aerial vehicles,image sensors,object detection,object tracking,robot vision,video signal processing,uav,autonomous detection,moving camera,moving objects tracking,video analytics,autonomous object detection,mobile visual surveillance platform,optical imaging,detectors,feature extraction,clustering algorithms,tracking,robustness | Conference | 4 |
PageRank | References | Authors |
0.46 | 21 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Pouria Sadeghi-Tehran | 1 | 65 | 6.26 |
| Christopher Clarke | 2 | 21 | 2.75 |
| Plamen Angelov | 3 | 954 | 67.44 |