Details
| Original language | English |
|---|---|
| Title of host publication | Robot Vision |
| Subtitle of host publication | International Workshop RobVis 2001, Proceedings |
| Publisher | Springer Verlag |
| Pages | 9-18 |
| Number of pages | 10 |
| ISBN (print) | 3540416943 |
| Publication status | Published - 12 Jun 2001 |
| Externally published | Yes |
| Event | International Workshop on Robot Vision, RobVis 2001 - Auckland, New Zealand Duration: 16 Feb 2001 → 18 Feb 2001 |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Volume | 1998 |
| ISSN (Print) | 0302-9743 |
| ISSN (electronic) | 1611-3349 |
Abstract
In this paper we apply a novel pose estimation algorithm to the tracking problem. We make use of error measures of the algorithm which enable us to characterize the quality of an estimated pose. The key idea of the tracking algorithm is random start local search. The principle of the heuristic relies upon a combination of iterative improvement and random sampling. While in many approaches a manually designed object representation is assumed, we overcome this condition by using accumulated object representations and combine these successfully with the tracking algorithm.
ASJC Scopus subject areas
- Mathematics(all)
- Theoretical Computer Science
- Computer Science(all)
- General Computer Science
Cite this
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Robot Vision: International Workshop RobVis 2001, Proceedings. Springer Verlag, 2001. p. 9-18 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1998).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Tracking with a novel pose estimation algorithm
AU - Rosenhahn, Bodo
AU - Krüger, Norbert
AU - Rabsch, Torge
AU - Sommer, Gerald
PY - 2001/6/12
Y1 - 2001/6/12
N2 - In this paper we apply a novel pose estimation algorithm to the tracking problem. We make use of error measures of the algorithm which enable us to characterize the quality of an estimated pose. The key idea of the tracking algorithm is random start local search. The principle of the heuristic relies upon a combination of iterative improvement and random sampling. While in many approaches a manually designed object representation is assumed, we overcome this condition by using accumulated object representations and combine these successfully with the tracking algorithm.
AB - In this paper we apply a novel pose estimation algorithm to the tracking problem. We make use of error measures of the algorithm which enable us to characterize the quality of an estimated pose. The key idea of the tracking algorithm is random start local search. The principle of the heuristic relies upon a combination of iterative improvement and random sampling. While in many approaches a manually designed object representation is assumed, we overcome this condition by using accumulated object representations and combine these successfully with the tracking algorithm.
UR - http://www.scopus.com/inward/record.url?scp=84945132099&partnerID=8YFLogxK
U2 - 10.1007/3-540-44690-7_2
DO - 10.1007/3-540-44690-7_2
M3 - Conference contribution
AN - SCOPUS:84945132099
SN - 3540416943
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 9
EP - 18
BT - Robot Vision
PB - Springer Verlag
T2 - International Workshop on Robot Vision, RobVis 2001
Y2 - 16 February 2001 through 18 February 2001
ER -