Sparse binarised statistical dynamic features for spatio-temporal texture analysis

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buir.contributor.authorArashloo, Shervin Rahimzadeh
dc.citation.epage582en_US
dc.citation.issueNumber3en_US
dc.citation.spage575en_US
dc.citation.volumeNumber13en_US
dc.contributor.authorArashloo, Shervin Rahimzadehen_US
dc.date.accessioned2020-01-31T12:48:41Z
dc.date.available2020-01-31T12:48:41Z
dc.date.issued2019
dc.departmentDepartment of Computer Engineeringen_US
dc.description.abstractThe paper presents a new spatio-temporal learning-based descriptor called binarised statistical dynamic features (BSDF) for representation and classification of dynamic texture. The BSDF descriptor operates by applying three-dimensional spatio-temporal filters on local voxels of an image sequence where the filters are learned via an independent component analysis, maximising independence over spatial and temporal domains concurrently. The BSDF representation is formed by binarising filter responses which are then converted into codewords and summarised using histograms. A robust representation of the BSDF descriptor is finally obtained via a sparse representation approach yielding very discriminative features for classification. The effects of different hyper-parameters on performance including the number of filters, the number of scales, temporal depth, number of samples drawn are also investigated. The proposed approach is evaluated on the most commonly used dynamic texture databases and shown to perform very well compared to the existing methods.en_US
dc.description.provenanceSubmitted by Zeynep Aykut (zeynepay@bilkent.edu.tr) on 2020-01-31T12:48:41Z No. of bitstreams: 1 Sparse_binarised_statistical_dynamic_features_for_spatio-temporal_texture_analysis.pdf: 582787 bytes, checksum: e8bf05f7d91e01af007b572ec5dfbe0d (MD5)en
dc.description.provenanceMade available in DSpace on 2020-01-31T12:48:41Z (GMT). No. of bitstreams: 1 Sparse_binarised_statistical_dynamic_features_for_spatio-temporal_texture_analysis.pdf: 582787 bytes, checksum: e8bf05f7d91e01af007b572ec5dfbe0d (MD5) Previous issue date: 2019en
dc.identifier.doi10.1007/s11760-018-1384-8en_US
dc.identifier.issn1863-1703
dc.identifier.urihttp://hdl.handle.net/11693/52954
dc.language.isoEnglishen_US
dc.publisherSpringeren_US
dc.relation.isversionofhttps://dx.doi.org/10.1007/s11760-018-1384-8en_US
dc.source.titleSignal, Image and Video Processingen_US
dc.subjectDynamic textureen_US
dc.subjectSpatio-temporal filteringen_US
dc.subjectIndependent component analysisen_US
dc.subjectSparse representationen_US
dc.titleSparse binarised statistical dynamic features for spatio-temporal texture analysisen_US
dc.typeArticleen_US

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