Real-time visual tracking using compressive sensing

Simple item page
dc.contributor.authorLi, Hanxi
dc.contributor.authorShen, Chunhua
dc.contributor.authorShi, Qinfeng
dc.coverage.spatialColorado Springs USA
dc.date.accessioned2015-12-10T23:11:12Z
dc.date.createdJune 21-23 2011
dc.date.issued2011
dc.date.updated2016-02-24T11:03:26Z
dc.description.abstractThe ℓ1 tracker obtains robustness by seeking a sparse representation of the tracking object via ℓ1 norm minimization. However, the high computational complexity involved in the 1 tracker may hamper its applications in real-time processing scenarios. H
dc.identifier.isbn9781457703942
dc.identifier.urihttp://hdl.handle.net/1885/63712
dc.publisherIEEE Computer Society
dc.relation.ispartofseriesIEEE Conference on Computer Vision and Pattern Recognition (CVPR 2011)
dc.sourceGraph connectivity in sparse subspace clustering
dc.subjectKeywords: Background model; Dimensionality reduction; Orthogonal matching pursuit; Real time; Realtime processing; Signal recovery; Sparse representation; Stationary cameras; Tracking accuracy; Tracking objects; Video sequences; Visual Tracking; Algorithms; Computa
dc.titleReal-time visual tracking using compressive sensing
dc.typeConference paper
local.bibliographicCitation.lastpage1312
local.bibliographicCitation.startpage1305
local.contributor.affiliationLi, Hanxi, College of Engineering and Computer Science, ANU
local.contributor.affiliationShen, Chunhua, NICTA
local.contributor.affiliationShi, Qinfeng, University of Adelaide
local.contributor.authoremailrepository.admin@anu.edu.au
local.contributor.authoruidLi, Hanxi, u4437149
local.description.embargo2037-12-31
local.description.notesImported from ARIES
local.description.refereedYes
local.identifier.absfor080104 - Computer Vision
local.identifier.absseo970109 - Expanding Knowledge in Engineering
local.identifier.ariespublicationu4334215xPUB839
local.identifier.doi10.1109/CVPR.2011.5995483
local.identifier.scopusID2-s2.0-80052901898
local.identifier.uidSubmittedByu4334215
local.type.statusPublished Version

Downloads

Original bundle

Now showing 1 - 1 of 1
No Thumbnail Available
Name:
01_Li_Real-time_visual_tracking_2011.pdf
Size:
439.66 KB
Format:
Adobe Portable Document Format
Download

Collections

ANU Research Publications

DSpace software copyright © 2002-2024 LYRASIS