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

@article{Das2020UtilityAP,
  title={Utility and Privacy in Object Tracking from Video Stream using Kalman Filter},
  author={Niladri Das and R. Bhattacharya},
  journal={2020 IEEE 23rd International Conference on Information Fusion (FUSION)},
  year={2020},
  pages={1-6}
}
  • Niladri Das, R. Bhattacharya
  • Published 15 June 2020
  • Computer Science
  • 2020 IEEE 23rd International Conference on Information Fusion (FUSION)
Tracking objects in Computer Vision is a hard problem. Privacy and utility concerns adds an extra layer of complexity over this problem. In this work we consider the problem of maintaining privacy and utility while tracking an object in a video stream using Kalman filtering. Our first proposed method ensures that the localization accuracy of this object will not improve beyond a certain level. Our second method ensures that the localization accuracy of the same object will always remain under a… 
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