A computer vision based camera pedestal's vertical motion control

Yi Da Xu, Joshua Brown, Jason Traish, Daniel Dezwa

Research output: Book chapter/Published conference paperConference paperpeer-review

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Traditional camera pedestals are manually operated. Our long term goal is to construct a fully autonomous pedestal system which can respond to changes in a scene and mimicking the human camera operator. In this paper, we discuss our experiments to control the vertical motion of a pedestal by leveling its position with a human head or a tracked hand-held object. We describe a set of computer vision methods used in these experiments, including the head position tracking using Gaussian mixture model (GMM) of the foreground blob and hand-held object tracking using continuously adaptive mean shift (CAM-shift) with motion initialization. We also discuss the application of Kalman filter and showing its effect in the reduction of the number of jittering pedestal motions.
Original languageEnglish
Title of host publicationIEEE International Conference on Pattern Recognition (ICPR)
Place of PublicationUSA
Number of pages4
Publication statusPublished - 2008
EventICPR 2008: 19th International Conference - Florida, USA, New Zealand
Duration: 08 Dec 200811 Dec 2008


ConferenceICPR 2008: 19th International Conference
CountryNew Zealand

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