State-of-the-Art: Transformation Invariant Descriptors

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State-of-the-Art: Transformation Invariant Descriptors

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dc.contributor.author Sreeraj, M
dc.contributor.author Asha, S
dc.date.accessioned 2014-07-30T06:14:30Z
dc.date.available 2014-07-30T06:14:30Z
dc.date.issued 2013-09
dc.identifier.issn 2229-5518
dc.identifier.uri http://dyuthi.cusat.ac.in/purl/4319
dc.description International Journal of Scientific & Engineering Research, Volume 4, Issue 9, september 2013 en_US
dc.description.abstract As the popularity of digital videos increases, a large number illegal videos are being generated and getting published. Video copies are generated by performing various sorts of transformations on the original video data. For effectively identifying such illegal videos, the image features that are invariant to various transformations must be extracted for performing similarity matching. An image feature can be its local feature or global feature. Among them, local features are powerful and have been applied in a wide variety of computer vision aplications .This paper focuses on various recently proposed local detectors and descriptors that are invariant to a number of image transformations. en_US
dc.language.iso en en_US
dc.publisher IJSER en_US
dc.subject Visual Matching en_US
dc.subject Interest Points en_US
dc.subject global features en_US
dc.subject Local Features en_US
dc.subject Feature Descriptors en_US
dc.subject Transformation en_US
dc.title State-of-the-Art: Transformation Invariant Descriptors en_US
dc.type Article en_US


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