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Image Processing and Computer Vision in Basketball Detection and Tracking

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dc.contributor.advisorVanderbei, Robert
dc.contributor.authorChai, Hanfu
dc.date.accessioned2014-07-16T18:34:48Z
dc.date.accessioned2026-09-30T00:04:33Z
dc.date.available2014-07-16T18:34:48Z
dc.date.available2026-09-30T00:04:33Z
dc.date.created2014-06
dc.date.issued2014-07-16
dc.description.abstractThis thesis uses a two-stage framework to detect and track a basketball in video footage. In the first stage, the ball is detected in each frame of the video sequence using different feature-based methods. Color-based, shape-based, and combined features methods are tested to determine the superior ball detection algorithm. In the second stage, the trajectory of the ball is tracked throughout the video sequence using a Kalman filter based candidate verification procedure.en_US
dc.format.extent71en_US
dc.identifier.urihttp://arks.princeton.edu/ark:/88435/dsp01nk322d52v
dc.identifier.urihttps://theses-dissertations.princeton.edu/handle/88435/dsp01nk322d52v
dc.language.isoen_USen_US
dc.titleImage Processing and Computer Vision in Basketball Detection and Trackingen_US
dc.typePrinceton University Senior Theses
dspace.entity.typePublication
pu.date.classyear2014en_US
pu.departmentOperations Research and Financial Engineeringen_US

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Operations Research and Financial Engineering, 2000-2026