Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/261373
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dc.coverage.spatialOcclusion Handling In 2D and 3D Object Recognition
dc.date.accessioned2019-10-10T09:01:25Z-
dc.date.available2019-10-10T09:01:25Z-
dc.identifier.urihttp://hdl.handle.net/10603/261373-
dc.description.abstractComputer vision is the science of endowing computers or othermachines with vision, or the ability to see. It is concerned with the extraction,analysis and understanding of useful information from an individual image ora set of images. Object recognition is one of the fundamental tasks incomputer vision and is the process of finding or identifying instances ofobjects in digital images or videos. These could be, for example, humans, newlineanimals and static or moving objects.Object recognition methods frequently use extracted features andlearning algorithms to recognize instances of an object or images belonging toan object category. Variations in lighting conditions, viewpoint, background newlineas well as occlusion where the object is not fully visible can change theobserved image immensely. Many of these existing algorithms work well inconstrained scenarios with specific assumptions regarding object appearance,background color intensity information, duration of time for which an objectexists in the scene and/or limitation regarding number of objects within thescene. newline newline
dc.format.extentxxvii, 130p.
dc.languageEnglish
dc.relationp.117-129
dc.rightsuniversity
dc.titleOcclusion Handling In 2D and 3D Object Recognition
dc.title.alternative
dc.creator.researcherPriya L
dc.subject.keywordEngineering and Technology,Computer Science,Computer Science Information Systems
dc.subject.keywordObject Recognition
dc.subject.keywordOcclusion Handling 30-Sep-2018
dc.description.note
dc.contributor.guideSheila Anand
dc.publisher.placeChennai
dc.publisher.universityAnna University
dc.publisher.institutionFaculty of Information and Communication Engineering
dc.date.registeredn.d.
dc.date.completed2018
dc.date.awarded30/09/2018
dc.format.dimensions21cm
dc.format.accompanyingmaterialNone
dc.source.universityUniversity
dc.type.degreePh.D.
Appears in Departments:Faculty of Information and Communication Engineering

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01_title.pdfAttached File22.94 kBAdobe PDFView/Open
02_certificates.pdf286.92 kBAdobe PDFView/Open
03_abstract.pdf7.66 kBAdobe PDFView/Open
04_acknowledgement.pdf4.52 kBAdobe PDFView/Open
05_contents.pdf13.74 kBAdobe PDFView/Open
06_list_of_symbols_and_abbreviations.pdf24.1 kBAdobe PDFView/Open
07_chapter1.pdf545.2 kBAdobe PDFView/Open
08_chapter2.pdf474.25 kBAdobe PDFView/Open
09_chapter3.pdf754.23 kBAdobe PDFView/Open
10_chapter4.pdf495.46 kBAdobe PDFView/Open
11_chapter5.pdf37.29 kBAdobe PDFView/Open
12_appendices.pdf817.36 kBAdobe PDFView/Open
13_references.pdf266.44 kBAdobe PDFView/Open
14_publications.pdf89.41 kBAdobe PDFView/Open


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