Name
Title | ||
|---|---|---|
Active visual-based detection and tracking of moving objects from clustering and classification methods |
Abstract | ||
|---|---|---|
This paper describes a method proposed for the detection, the tracking and the identification of mobile objects, detected from a mobile camera, typically a camera embedded on a robot. A global architecture is presented, using only vision, in order to solve simultaneously several problems: the camera (or vehicle) Localization, the environment Mapping and the Detection and Tracking of Moving Objects. The goal is to build a convenient description of a dynamic scene from vision: what is static? What is dynamic? where is the robot? how do other mobile objects move? It is proposed to combine two approaches; first a Clustering method allows to detect static points, to be used by the SLAM algorithm and dynamic ones, to segment and estimate the status of mobile objects. Second a classification approach allows to identify objects of known classes in image regions. These two approaches are combined in an active method based in a Motion Grid in order to select actively where to look for mobile objects. The overall approach is evaluated with real data acquired indoor and outdoor from a camera embedded on a mobile robot. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1007/978-3-642-33140-4_32 | ACIVS |
Keywords | DocType | Citations |
active visual-based detection,mobile robot,classification method,dynamic scene,clustering method,mobile objects move,static point,overall approach,active method,mobile camera,classification approach,mobile object | Conference | 1 |
PageRank | References | Authors |
0.36 | 13 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| David M. Evans | 1 | 34 | 8.31 |
| rquez-G$#225 | 2 | 1 | 0.36 |
| mez | 3 | 1 | 0.36 |
| Michel Devy | 4 | 542 | 71.47 |