Please use this identifier to cite or link to this item: https://idr.l1.nitk.ac.in/jspui/handle/123456789/7435
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dc.contributor.authorPais, A.R.
dc.contributor.authorPasupuleti, N.
dc.contributor.authorGidnavar, R.
dc.contributor.authorD'Souza, J.
dc.date.accessioned2020-03-30T09:59:06Z-
dc.date.available2020-03-30T09:59:06Z-
dc.date.issued2009
dc.identifier.citationProceedings of the 4th Indian International Conference on Artificial Intelligence, IICAI 2009, 2009, Vol., , pp.2007-2021en_US
dc.identifier.urihttp://idr.nitk.ac.in/jspui/handle/123456789/7435-
dc.description.abstractDetecting, segmenting and super resolving of moving object is an important subject in computer visual analysis and surveillance. This paper discusses automatic VOP (Video Object Plane) segmentation and super resolving of VOP. We have proposed a new method for automatic generation of VOP by using block matching and quantization techniques. Edge model based approach is used to generate the HR (High Resolution) image with sharper VOP boundaries. Experimental results show that the proper VOP is segmented and super resolution of VOP yields lesser blurring compared to bicubic, bilinear interpolation schemes. Copyright � 2009 by IICAI.en_US
dc.titleAutomatic video object plane segmentation and super resolution: A novel approachen_US
dc.typeBook chapteren_US
Appears in Collections:2. Conference Papers

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