Action recognition in video using sparse coding and relative features

dc.date.accessioned2018-12-07T13:33:15Z
dc.date.accessioned2022-10-18T21:57:28Z
dc.date.available2018-12-07T13:33:15Z
dc.date.available2022-10-18T21:57:28Z
dc.date.created2018-12-07T13:33:15Z
dc.date.issued2016
dc.identifierhttp://hdl.handle.net/10533/232383
dc.identifier1151077
dc.identifierWOS:000400012302080
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/4463738
dc.description.abstractThis 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.languageeng
dc.relationhttp://openaccess.thecvf.com/content_cvpr_2016/papers/Alfaro_Action_Recognition_in_CVPR_2016_paper.pdf
dc.relationhandle/10533/111557
dc.relation10.1109/CVPR.2016.294
dc.relationhandle/10533/111541
dc.relationhandle/10533/108045
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 Chile
dc.rightshttp://creativecommons.org/licenses/by-nc-nd/3.0/cl/
dc.titleAction recognition in video using sparse coding and relative features
dc.typeArticulo


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