Region-based moving object detection using spatially conditioned nonparametric models in a GPU
Data(s) |
2014
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Resumo |
A novel GPU-based nonparametric moving object detection strategy for computer vision tools requiring real-time processing is proposed. An alternative and efficient Bayesian classifier to combine nonparametric background and foreground models allows increasing correct detections while avoiding false detections. Additionally, an efficient region of interest analysis significantly reduces the computational cost of the detections. |
Formato |
application/pdf |
Identificador | |
Idioma(s) |
eng |
Publicador |
E.T.S.I. Telecomunicación (UPM) |
Relação |
http://oa.upm.es/36200/1/INVE_MEM_2014_199229.pdf http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6776041&tag=1 info:eu-repo/semantics/altIdentifier/doi/null |
Direitos |
http://creativecommons.org/licenses/by-nc-nd/3.0/es/ info:eu-repo/semantics/openAccess |
Fonte |
IEEE International Conference on Consumer Electronics (ICCE 2014) | IEEE International Conference on Consumer Electronics (ICCE 2014) | 10/01/2014 - 13/01/2014 | Las Vegas, Nevada, USA |
Palavras-Chave | #Telecomunicaciones |
Tipo |
info:eu-repo/semantics/conferenceObject Ponencia en Congreso o Jornada PeerReviewed |