A novel zoom invariant video object tracking algorithm (ZIVOTA)

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dc.contributor.advisorBadawy, Wael
dc.contributor.authorWei, Yankun
dc.date.accessioned2005-08-08T19:57:47Z
dc.date.available2005-08-08T19:57:47Z
dc.date.issued2003
dc.descriptionBibliography: p. 82-88en
dc.description.abstractAdvanced surveillance system should have the ability to track targets that have non-rigid shape and structure/size. A limitation in the field of real-time target tracking is the high computation load, so the tracking algorithms are difficult to be implemented on an ordinary personal computer without any special-purpose hardware component. This thesis presents a real-time zoom-invariant video object tracking algorithm (ZIVOTA). It can be used to track human or rigid-shaped object. ZIVOTA can provide information of object-of-interest while performing tracking, which enables automatic visual system control. It employs the same set of features to track both the position and size of a moving object through frames. Time-consuming processes like feature detection and affine basis set selection will be done only when it is necessary. Computational load is largely reduced. By using affine motion model, this technique is fundamentally zoom-invariant, it can deal with translation, rotation, and scaling of objects. Since the gaze point (representing the object location) and object boundary points (representing the object size) are virtual, ZIV OT A is able to handle partial occlusion.
dc.format.extentx, 88 leaves : ill. ; 30 cm.en
dc.identifier.citationWei, Y. (2003). A novel zoom invariant video object tracking algorithm (ZIVOTA) (Master's thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca. doi:10.11575/PRISM/20605en_US
dc.identifier.doihttp://dx.doi.org/10.11575/PRISM/20605
dc.identifier.urihttp://hdl.handle.net/1880/39967
dc.language.isoeng
dc.publisher.institutionUniversity of Calgaryen
dc.publisher.placeCalgaryen
dc.rightsUniversity of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.
dc.titleA novel zoom invariant video object tracking algorithm (ZIVOTA)
dc.typemaster thesis
thesis.degree.disciplineElectrical and Computer Engineering
thesis.degree.grantorUniversity of Calgary
thesis.degree.nameMaster of Science (MSc)
ucalgary.item.requestcopytrue
ucalgary.thesis.accessionTheses Collection 58.002:Box 1480 520708915
ucalgary.thesis.notesUARCen
ucalgary.thesis.uarcreleaseyen
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