GPU acceleration of the KAZE image feature extraction algorithm

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dc.contributor.author Ramkumar, B.
dc.contributor.author Laber, Rob
dc.contributor.author Bojinov, Hristo
dc.contributor.author Hegde, Ravi Sadananda
dc.date.accessioned 2019-03-27T06:42:08Z
dc.date.available 2019-03-27T06:42:08Z
dc.date.issued 2019-01
dc.identifier.citation Ramkumar, B.; Laber, Rob; Bojinov, Hristo and Hegde, Ravi Sadananda, “GPU acceleration of the KAZE image feature extraction algorithm”, Journal of Real-Time Image Processing, DOI: 10.1007/s11554-019-00861-2, vol. 17, no. 5, pp. 1169-1182, Mar. 2019. en_US
dc.identifier.issn 1861-8200
dc.identifier.issn 1861-8219
dc.identifier.uri https://doi.org/10.1007/s11554-019-00861-2
dc.identifier.uri https://repository.iitgn.ac.in/handle/123456789/4293
dc.description.abstract GPU in comparison to nearly 2400 ms for a 16-threaded CPU version) without degradation in feature extraction performance, our work expands the applicability of the KAZE algorithm. Additionally, the strategies described here could also prove useful for the GPU implementation of other nonlinear scale-space-based image processing algorithms.
dc.description.statementofresponsibility by B. Ramkumar, Rob Laber, Hristo Bojinov and Ravi Sadananda Hegde
dc.language.iso en en_US
dc.publisher American Chemical Society en_US
dc.subject Nonlinear scale space en_US
dc.subject Feature detection en_US
dc.subject Feature description en_US
dc.subject GPU acceleration en_US
dc.subject KAZE features en_US
dc.title GPU acceleration of the KAZE image feature extraction algorithm en_US
dc.type Article en_US
dc.relation.journal Journal of Real-Time Image Processing


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