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020 _a9783319520810
_9978-3-319-52081-0
024 7 _a10.1007/978-3-319-52081-0
_2doi
050 4 _aQ342
072 7 _aUYQ
_2bicssc
072 7 _aTEC009000
_2bisacsh
072 7 _aUYQ
_2thema
082 0 4 _a006.3
_223
245 1 0 _aRecent Advances in Intelligent Image Search and Video Retrieval
_h[electronic resource] /
_cedited by Chengjun Liu.
250 _a1st ed. 2017.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2017.
300 _aXVII, 235 p. 88 illus., 85 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aIntelligent Systems Reference Library,
_x1868-4408 ;
_v121
505 0 _aFeature Representation and Extraction for Image Search and Video Retrieval -- Learning and Recognition Methods for Image Search and Video Retrieval -- Improved Soft Assignment Coding for Image Classification -- Inheritable Color Space (InCS) and Generalized InCS Framework with Applications to Kinship Verification -- Novel Sparse Kernel Manifold Learner for Image Classification Applications -- A New Efficient SVM (eSVM) with Applications to Accurate and Efficient Eye Search in Images -- SIFT Features in Multiple Color Spaces for Improved Image Classification -- Clothing Analysis for Subject Identification and Retrieval -- Performance Evaluation of Video Analytics for Traffic Incident Detection and Vehicle Counts Collection.
520 _aThis book initially reviews the major feature representation and extraction methods and effective learning and recognition approaches, which have broad applications in the context of intelligent image search and video retrieval. It subsequently presents novel methods, such as improved soft assignment coding, Inheritable Color Space (InCS) and the Generalized InCS framework, the sparse kernel manifold learner method, the efficient Support Vector Machine (eSVM), and the Scale-Invariant Feature Transform (SIFT) features in multiple color spaces. Lastly, the book presents clothing analysis for subject identification and retrieval, and performance evaluation methods of video analytics for traffic monitoring. Digital images and videos are proliferating at an amazing speed in the fields of science, engineering and technology, media and entertainment. With the huge accumulation of such data, keyword searches and manual annotation schemes may no longer be able to meet the practical demand for retrieving relevant content from images and videos, a challenge this book addresses.
650 0 _aComputational intelligence.
_97716
650 0 _aComputer vision.
_962676
650 0 _aArtificial intelligence.
_93407
650 1 4 _aComputational Intelligence.
_97716
650 2 4 _aComputer Vision.
_962677
650 2 4 _aArtificial Intelligence.
_93407
700 1 _aLiu, Chengjun.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_962678
710 2 _aSpringerLink (Online service)
_962679
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783319520803
776 0 8 _iPrinted edition:
_z9783319520827
776 0 8 _iPrinted edition:
_z9783319848167
830 0 _aIntelligent Systems Reference Library,
_x1868-4408 ;
_v121
_962680
856 4 0 _uhttps://doi.org/10.1007/978-3-319-52081-0
912 _aZDB-2-ENG
912 _aZDB-2-SXE
942 _cEBK
999 _c81019
_d81019