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Motion segmentation & multiple object tracking by correlation co-clustering
Keuper, Margret
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Tang, Siyu
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Andres, Björn
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Brox, Thomas
;
Schiele, Bernt
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DOI:
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https://doi.org/10.1109/TPAMI.2018.2876253
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URL:
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https://ieeexplore.ieee.org/document/8493320/
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Document Type:
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Article
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Year of publication:
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2020
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The title of a journal, publication series:
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IEEE Transactions on Pattern Analysis and Machine Intelligence
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Volume:
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42
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Issue number:
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1
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Page range:
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140-153
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Place of publication:
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New York, NY
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Publishing house:
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IEEE Computer Society
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ISSN:
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0162-8828 , 1939-3539
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Publication language:
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English
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Institution:
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School of Business Informatics and Mathematics > Bildverarbeitung (Juniorprofessur) (Keuper 2017-2021)
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Subject:
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004 Computer science, internet
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Keywords (English):
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Clustering algorithms , Computer vision , Correlation , Motion segmentation , Object tracking , Trajectory
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Abstract:
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Models for computer vision are commonly defined either w.r.t. low-level concepts such as pixels that are to be grouped, or w.r.t. high-level concepts such as semantic objects that are to be detected and tracked. Combining bottom-up grouping with top-down detection and tracking, although highly desirable, is a challenging problem. We state this joint problem as a co-clustering problem that is principled and tractable by existing algorithms. We demonstrate the effectiveness of this approach by combining bottom-up motion segmentation by grouping of point trajectories with high-level multiple object tracking by clustering of bounding boxes. We show that solving the joint problem is beneficial at the low-level, in terms of the FBMS59 motion segmentation benchmark, and at the high-level, in terms of the Multiple Object Tracking benchmarks MOT15, MOT16 and the MOT17 challenge, and is state-of-the-art in some metrics.
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 | Dieser Eintrag ist Teil der Universitätsbibliographie. |
 Search Authors in
BASE:
Keuper, Margret
;
Tang, Siyu
;
Andres, Björn
;
Brox, Thomas
;
Schiele, Bernt
Google Scholar:
Keuper, Margret
;
Tang, Siyu
;
Andres, Björn
;
Brox, Thomas
;
Schiele, Bernt
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