DUGiDocsEnhanced Model Selection for motion segmentation
dc.contributor.author
dc.date.accessioned
2010-05-10T12:18:05Z
dc.date.available
2010-05-03T15:18:06Z
2010-05-10T12:18:05Z
dc.date.issued
2009
dc.identifier.citation
Zappella, L., Llado, X., i Salvi, J. (2009). Enhanced Model Selection for motion segmentation. 16th IEEE International Conference on Image Processing (ICIP) : 2009, 4053-4056. Recuperat 10 maig 2010, a http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5413729
dc.identifier.isbn
978-1-4244-5655-0
dc.identifier.issn
1522-4880
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dc.description.abstract
In this paper a novel rank estimation technique for trajectories motion segmentation within the Local Subspace Affinity (LSA) framework is presented. This technique, called Enhanced Model Selection (EMS), is based on the relationship between the estimated rank of the trajectory matrix and the affinity matrix built by LSA. The results on synthetic and real data show that without any a priori knowledge, EMS automatically provides an accurate and robust rank estimation, improving the accuracy of the final motion segmentation
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application/pdf
dc.language.iso
eng
dc.publisher
IEEE
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Reproducció digital del document publicat a: http://dx.doi.org/10.1109/ICIP.2009.5413729
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© 16th IEEE International Conference on Image Processing (ICIP), 2009, p. 4053-4056
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Articles publicats (D-ATC)
dc.rights
Tots els drets reservats
dc.subject
dc.title
Enhanced Model Selection for motion segmentation
dc.type
info:eu-repo/semantics/article
dc.rights.accessRights
info:eu-repo/semantics/openAccess
dc.identifier.doi