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Utility and Privacy in Object Tracking from Video Stream using Kalman Filter

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Document pages: 6 pages

Abstract: Tracking objects in Computer Vision is a hard problem. Privacy and utilityconcerns adds an extra layer of complexity over this problem. In this work weconsider the problem of maintaining privacy and utility while tracking anobject in a video stream using Kalman filtering. Our first proposed methodensures that the localization accuracy of this object will not improve beyond acertain level. Our second method ensures that the localization accuracy of thesame object will always remain under a certain threshold.

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