Show simple item record

dc.contributor.authorLi, Xin
dc.contributor.authorDutta, Aritra
dc.date.accessioned2018-12-31T13:08:49Z
dc.date.available2018-12-31T13:08:49Z
dc.date.issued2018-01-22
dc.identifier.citationLi X, Dutta A (2017) Weighted Low Rank Approximation for Background Estimation Problems. 2017 IEEE International Conference on Computer Vision Workshops (ICCVW). Available: http://dx.doi.org/10.1109/ICCVW.2017.219.
dc.identifier.doi10.1109/ICCVW.2017.219
dc.identifier.urihttp://hdl.handle.net/10754/630413
dc.description.abstractClassical principal component analysis (PCA) is not robust when the data contain sparse outliers. The use of the ℓ1 norm in the Robust PCA (RPCA) method successfully eliminates this weakness of PCA in separating the sparse outliers. Here we propose a weighted low rank (WLR) method, where a simple weight is inserted inside the Frobenius norm. We demonstrate how this method tackles often computationally expensive algorithms that rely on the ℓ1 norm. As a proof of concept, we present a background estimation model based on WLR, and we compare the model with RPCA method and with other state-of-the-art algorithms used for background estimation. Our empirical validation shows that the weighted low-rank approximation we propose here can perform as well as or better than that of RPCA and other state-of-the-art algorithms.
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.relation.urlhttps://ieeexplore.ieee.org/document/8265429/
dc.titleWeighted Low Rank Approximation for Background Estimation Problems
dc.typeConference Paper
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.identifier.journal2017 IEEE International Conference on Computer Vision Workshops (ICCVW)
dc.conference.date2017-10-22 to 2017-10-29
dc.conference.name16th IEEE International Conference on Computer Vision Workshops, ICCVW 2017
dc.conference.locationVenice, ITA
dc.contributor.institutionUniversity of Central Florida, , United States
dc.identifier.arxivid1707.01753
kaust.personDutta, Aritra
dc.date.published-online2018-01-22
dc.date.published-print2017-10


This item appears in the following Collection(s)

Show simple item record