Details
| Original language | English |
|---|---|
| Title of host publication | Pattern Recognition |
| Subtitle of host publication | 36th German Conference, GCPR 2014, Proceedings |
| Publisher | Springer Verlag |
| Pages | 265-276 |
| Number of pages | 12 |
| ISBN (electronic) | 9783319117515 |
| Publication status | Published - 15 Oct 2014 |
| Event | 36th German Conference on Pattern Recognition, GCPR 2014 - Münster, Germany Duration: 2 Sept 2014 → 5 Sept 2014 |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Volume | 8753 |
| ISSN (Print) | 0302-9743 |
| ISSN (electronic) | 1611-3349 |
Abstract
We present a new global optimization approach for multiple people tracking based on a hierarchical tracklet framework. A new type of tracklets is introduced, which we call tree tracklets. They contain bifurcations to naturally deal with ambiguous tracking situations. Difficult decisions are postponed to a later iteration of the hierarchical framework, when more information is available.We cast the optimization problem as a minimum cost arborescence problem in an acyclic directed graph, where a tracking solution can be obtained in linear time. Experiments on six publicly available datasets show that the method performs well when compared to state-of-the art tracking algorithms.
ASJC Scopus subject areas
- Mathematics(all)
- Theoretical Computer Science
- Computer Science(all)
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Pattern Recognition: 36th German Conference, GCPR 2014, Proceedings. Springer Verlag, 2014. p. 265-276 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8753).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Efficient multiple people tracking using minimum cost arborescences
AU - Henschel, Roberto
AU - Leal-Taixé, Laura
AU - Rosenhahn, Bodo
PY - 2014/10/15
Y1 - 2014/10/15
N2 - We present a new global optimization approach for multiple people tracking based on a hierarchical tracklet framework. A new type of tracklets is introduced, which we call tree tracklets. They contain bifurcations to naturally deal with ambiguous tracking situations. Difficult decisions are postponed to a later iteration of the hierarchical framework, when more information is available.We cast the optimization problem as a minimum cost arborescence problem in an acyclic directed graph, where a tracking solution can be obtained in linear time. Experiments on six publicly available datasets show that the method performs well when compared to state-of-the art tracking algorithms.
AB - We present a new global optimization approach for multiple people tracking based on a hierarchical tracklet framework. A new type of tracklets is introduced, which we call tree tracklets. They contain bifurcations to naturally deal with ambiguous tracking situations. Difficult decisions are postponed to a later iteration of the hierarchical framework, when more information is available.We cast the optimization problem as a minimum cost arborescence problem in an acyclic directed graph, where a tracking solution can be obtained in linear time. Experiments on six publicly available datasets show that the method performs well when compared to state-of-the art tracking algorithms.
UR - http://www.scopus.com/inward/record.url?scp=84908665267&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-11752-2_21
DO - 10.1007/978-3-319-11752-2_21
M3 - Conference contribution
AN - SCOPUS:84908665267
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 265
EP - 276
BT - Pattern Recognition
PB - Springer Verlag
T2 - 36th German Conference on Pattern Recognition, GCPR 2014
Y2 - 2 September 2014 through 5 September 2014
ER -