Name
Abstract | ||
|---|---|---|
This paper presents a robust tracking system for autonomous robots equipped with omnidirectional cameras. The proposed method uses a 3D shape and color-based object model. This allows to tackle difficulties that arise when the tracked object is placed above the ground plane floor. Tracking under these conditions has two major difficulties: first, observation with omnidirectional sensors largely deforms the target's shape; second, the object of interest embedded in a dynamic scenario may suffer from occlusion, overlap and ambiguities. To surmount these difficulties, we use a 3D particle filterto represent the target's state space: position and velocity with respect to the robot. To compute the likelihood of each particle the following features are taken into account: i) image color; ii) mismatch between target's color and background color. We test the accuracy of the algorithm in a RoboCup Middle Size League scenario, both with static and moving targets. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1007/978-3-540-68847-1_7 | RoboCup 2009 |
Keywords | Field | DocType |
particle filters,image color,tracked object,color-based object model,league scenario,robust tracking system,omnidirectional sensor,omnidirectional camera,background color,catadioptric vision,robocup middle size,dynamic scenario,tracking system,particle filter,state space,object model | Omnidirectional camera,Computer vision,Color histogram,Computer science,Simulation,Particle filter,Object model,Tracking system,Artificial intelligence,Robot,State space,Catadioptric system | Conference |
Volume | ISSN | Citations |
5001 | 0302-9743 | 5 |
PageRank | References | Authors |
0.50 | 12 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Matteo Taiana | 1 | 39 | 3.68 |
| José Gaspar | 2 | 48 | 5.28 |
| Jacinto C. Nascimento | 3 | 36 | 2.47 |
| Alexandre Bernardino | 4 | 710 | 78.77 |
| Pedro U. Lima | 5 | 516 | 69.88 |