Action recognition in video using sparse coding and relative features

2016 Ieee Conference On Computer Vision And Pattern Recognition (CVPR)

dc.creatorAlfaro, Anali
dc.creatorMery, Domingo
dc.creatorSoto, Alvaro
dc.date2018-12-07T13:33:15Z
dc.date2022-07-07T21:36:03Z
dc.date2015
dc.date2018-12-07T13:33:15Z
dc.date2022-07-07T21:36:03Z
dc.date2016
dc.date.accessioned2023-08-22T00:57:53Z
dc.date.available2023-08-22T00:57:53Z
dc.identifier1151077
dc.identifier1151077
dc.identifierhttps://hdl.handle.net/10533/232383
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/8303392
dc.descriptionThis work presents an approach to category-based action recognition in video using sparse coding techniques. The proposed approach includes two main contributions: i) A new method to handle intra-class variations by decomposing each video into a reduced
dc.descriptionRegular
dc.descriptionFONDECYT
dc.descriptionFONDECYT
dc.languageeng
dc.relationhandle/10533/111557
dc.relationhandle/10533/111541
dc.relationhandle/10533/108045
dc.relationhttp://openaccess.thecvf.com/content_cvpr_2016/papers/Alfaro_Action_Recognition_in_CVPR_2016_paper.pdf
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 Chile
dc.rightshttp://creativecommons.org/licenses/by-nc-nd/3.0/cl/
dc.rightsinfo:eu-repo/semantics/openAccess
dc.titleAction recognition in video using sparse coding and relative features
dc.title2016 Ieee Conference On Computer Vision And Pattern Recognition (CVPR)
dc.typeArticulo
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/publishedVersion


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