Details
| Originalsprache | Englisch |
|---|---|
| Titel des Sammelwerks | Pattern Recognition |
| Untertitel | 35th German Conference, GCPR 2013 |
| Herausgeber (Verlag) | Springer Heidelberg |
| Seiten | 425-434 |
| Seitenumfang | 10 |
| ISBN (elektronisch) | 978-3-642-40602-7 |
| ISBN (Print) | 978-3-642-40601-0 |
| Publikationsstatus | Veröffentlicht - 2013 |
| Veranstaltung | 35th German Conference on Pattern Recognition, GCPR 2013 - Saarbrücken, Deutschland Dauer: 3 Sept. 2013 → 6 Sept. 2013 |
Publikationsreihe
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Herausgeber (Verlag) | Springer Verlag |
| Band | 8142 |
| ISSN (Print) | 0302-9743 |
| ISSN (elektronisch) | 1611-3349 |
Abstract
In this paper, we analyze and modify the Motion-Split-and-Merge (MSAM) algorithm [3] for the motion segmentation of correspondences between two frames. Our goal is to make the algorithm suitable for practical use which means realtime processing speed at very low error rates. We compare our (robust realtime) RMSAM with J-Linkage [16] and Graph-Based Segmentation [5] and show that it is superior to both. Applying RMSAM in a multi-frame motion segmentation context to the Hopkins 155 benchmark, we show that compared to the original formulation, the error decreases from 2.05% to only 0.65% at a runtime reduced by 72%. The error is still higher than the best results reported so far, but RMSAM is dramatically faster and can handle outliers and missing data.
ASJC Scopus Sachgebiete
- Mathematik (insg.)
- Theoretische Informatik
- Informatik (insg.)
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Pattern Recognition: 35th German Conference, GCPR 2013. Springer Heidelberg, 2013. S. 425-434 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 8142).
Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review
}
TY - GEN
T1 - Robust Realtime Motion-Split-And-Merge for Motion Segmentation
AU - Dragon, Ralf
AU - Ostermann, Jörn
AU - Van Gool, Luc
PY - 2013
Y1 - 2013
N2 - In this paper, we analyze and modify the Motion-Split-and-Merge (MSAM) algorithm [3] for the motion segmentation of correspondences between two frames. Our goal is to make the algorithm suitable for practical use which means realtime processing speed at very low error rates. We compare our (robust realtime) RMSAM with J-Linkage [16] and Graph-Based Segmentation [5] and show that it is superior to both. Applying RMSAM in a multi-frame motion segmentation context to the Hopkins 155 benchmark, we show that compared to the original formulation, the error decreases from 2.05% to only 0.65% at a runtime reduced by 72%. The error is still higher than the best results reported so far, but RMSAM is dramatically faster and can handle outliers and missing data.
AB - In this paper, we analyze and modify the Motion-Split-and-Merge (MSAM) algorithm [3] for the motion segmentation of correspondences between two frames. Our goal is to make the algorithm suitable for practical use which means realtime processing speed at very low error rates. We compare our (robust realtime) RMSAM with J-Linkage [16] and Graph-Based Segmentation [5] and show that it is superior to both. Applying RMSAM in a multi-frame motion segmentation context to the Hopkins 155 benchmark, we show that compared to the original formulation, the error decreases from 2.05% to only 0.65% at a runtime reduced by 72%. The error is still higher than the best results reported so far, but RMSAM is dramatically faster and can handle outliers and missing data.
UR - http://www.scopus.com/inward/record.url?scp=84886438267&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-40602-7_45
DO - 10.1007/978-3-642-40602-7_45
M3 - Conference contribution
AN - SCOPUS:84886438267
SN - 978-3-642-40601-0
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 425
EP - 434
BT - Pattern Recognition
PB - Springer Heidelberg
T2 - 35th German Conference on Pattern Recognition, GCPR 2013
Y2 - 3 September 2013 through 6 September 2013
ER -