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Object tracking using statistical descriptors

dc.contributor.advisorJung, Claudio Rosito
dc.contributor.authorDihl, Leandro Lorenzettpt_BR
dc.date.accessioned2015-03-05T14:01:20Z
dc.date.accessioned2022-09-22T19:05:29Z
dc.date.available2015-03-05T14:01:20Z
dc.date.available2022-09-22T19:05:29Z
dc.date.issued2009-03-13
dc.identifier.urihttps://hdl.handle.net/20.500.12032/56810
dc.description.abstractThe low cost of image acquisition systems and increase the computational power of available machines have caused a growing demand for automated video analysis in several applications, such as surveillance, human-computer interfaces, analysis of sports performance, etc. Object tracking through the video sequence is part of this analysis, and it has been a challenging problem in the computer vision area. This work presents a new approach for object tracking based on fragments. Initially, the region selected for tracking is divided into rectangular subregions (patches, or fragments), and each patch is tracked independently. Moreover, the motion history of the object is used to estimate its position in the subsequent frames. The overall displacement of the object is then obtained combining the displacements of each patch and the predicted displacement vector in order to priorize fragments presenting consistent displacement. An update scheme is also applied to the model, to deal with illumination and appearance cen
dc.description.sponsorshipNenhumapt_BR
dc.languagept_BRpt_BR
dc.publisherUniversidade do Vale do Rio do Sinospt_BR
dc.rightsopenAccesspt_BR
dc.subjectdistância de Bhattacharyyapt_BR
dc.subjectBhattacharyya distanceen
dc.titleRastreamento de objetos usando descritores estatísticospt_BR
dc.titleObject tracking using statistical descriptorsen
dc.typeDissertaçãopt_BR


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