Patch-based detection of dynamic objects in CrowdCam images

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dc.contributor.author Kanojia, Gagan
dc.contributor.author Raman, Shanmuganathan
dc.date.accessioned 2018-02-15T10:21:41Z
dc.date.available 2018-02-15T10:21:41Z
dc.date.issued 2018-02
dc.identifier.citation Kanojia, Gagan and Raman, Shanmuganathan, “Patch-based detection of dynamic objects in CrowdCam images”, The Visual Computer, DOI: 10.1007/s00371-018-1480-3, Feb. 2018. en_US
dc.identifier.issn 0178-2789
dc.identifier.issn 1432-2315
dc.identifier.uri https://repository.iitgn.ac.in/handle/123456789/3463
dc.identifier.uri http://dx.doi.org/10.1007/s00371-018-1480-3
dc.description.abstract A scene can be divided into two parts: static and dynamic. The parts of the scene which do not admit any motion are static regions, while moving objects correspond to dynamic regions. In this work, we tackle the challenging task of identifying dynamic objects present in the CrowdCam images. Our approach exploits the coherency present in the natural images and utilizes the epipolar geometry present between a pair of images to achieve this objective. It does not require a dynamic object to be present in all the given images. We show that the proposed approach obtains state-of-the-art accuracy on standard datasets. en_US
dc.description.statementofresponsibility Gagan Kanojia and Shanmuganathan Raman
dc.language.iso en en_US
dc.publisher Springer Verlag en_US
dc.subject Object detection en_US
dc.subject Dynamic objects en_US
dc.subject Epipolar geometry en_US
dc.title Patch-based detection of dynamic objects in CrowdCam images en_US
dc.type Article en_US
dc.relation.journal Visual Computer


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