Name
Abstract | ||
|---|---|---|
This paper introduces DART, a general framework for tracking articulated objects composed of rigid bodies connected through a kinematic tree. DART covers a broad set of objects encountered in indoor environments, including furniture and tools, and human and robot bodies, hands and manipulators. To achieve efficient and robust tracking, DART extends the signed distance function representation to articulated objects and takes full advantage of highly parallel GPU algorithms for data association and pose optimization. We demonstrate the capabilities of DART on different types of objects that have each required dedicated tracking techniques in the past. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1007/s10514-015-9462-z | Autonomous Robots |
Keywords | Field | DocType |
Articulated model tracking,Signed distance function,Real-time vision,RGB-D | Computer vision,Kinematics,Computer graphics (images),Signed distance function,Simulation,Computer science,Dart,Real time vision,Data association,Artificial intelligence,Robot | Journal |
Volume | Issue | ISSN |
39 | 3 | 0929-5593 |
Citations | PageRank | References |
7 | 0.45 | 39 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tanner Schmidt | 1 | 65 | 4.15 |
| Richard A. Newcombe | 2 | 3003 | 111.68 |
| Dieter Fox | 3 | 12306 | 1289.74 |