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dc.contributor.advisorHe, Zhihai, 1973-eng
dc.contributor.authorWu, Dieng
dc.date.issued2013eng
dc.date.submitted2013 Falleng
dc.description"December 2013."eng
dc.description"A Thesis presented to the Faculty of the Graduate School at the University of Missouri In Partial Fulfillment of the Requirements for the Degree Master of Science."eng
dc.descriptionThesis supervisor: Dr. Zhihai He.eng
dc.description.abstractPedestrian detection and counting have important application in video surveillance for entrance monitoring, customer behavior analysis, and public service management. In this thesis, we propose an accurate, reliable and fast method for pedestrian detection and counting in video surveillance. To this end, we first develop an effective method for background modeling, subtraction, update, and shadow removal. To effectively differentiate person image patches from other background patches, we develop a head-shoulder classification and detection method. A foreground mask curve analysis method is to determine the possible position of persons, and then use a SVM (Support Vector Machine) classifier with HOG (Histogram of Oriented) feature and bag of words to detect the head-shoulder of people. Based on the foreground detection and head-shoulder classification at each frame, we develop a person counting algorithm in the temporal domain to analyze the frame-level classification results. Our experiments with real-world surveillance videos demonstrate the proposed method has achieved accurate and reliable pedestrian detection and counting.eng
dc.description.bibrefIncludes bibliographical references (pages 46-54).eng
dc.format.extent1 online resource (ix, 54 pages) : illustrations (some color)eng
dc.identifier.oclc899283068eng
dc.identifier.urihttps://hdl.handle.net/10355/43038
dc.identifier.urihttps://doi.org/10.32469/10355/43038eng
dc.languageEnglisheng
dc.publisherUniversity of Missouri--Columbiaeng
dc.relation.ispartofcommunityUniversity of Missouri--Columbia. Graduate School. Theses and Dissertationseng
dc.sourceSubmitted by the University of Missouri--Columbia Graduate Schooleng
dc.titlePedestrian detection and counting in surveillance videoseng
dc.typeThesiseng
thesis.degree.disciplineElectrical and computer engineering (MU)eng
thesis.degree.grantorUniversity of Missouri--Columbiaeng
thesis.degree.levelMasterseng
thesis.degree.nameM.S.eng


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