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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References

SHOWING 1-10 OF 14 REFERENCES
Object-Video Streams for Preserving Privacy in Video Surveillance
  • F. Qureshi
  • Computer Science
    2009 Sixth IEEE International Conference on Advanced Video and Signal Based Surveillance
  • 2009
TLDR
This paper presents a framework for preserving privacy in video surveillance by revealing the identities of some individuals, while preserving the anonymity of others in a virtual train station environment populated by autonomous, lifelike virtual pedestrians.
Technical Challenges in Location-Aware Video Surveillance Privacy
  • Jack Brassil
  • Computer Science
    Protecting Privacy in Video Surveillance
  • 2009
TLDR
The system – Cloak – seeks to discourage surveillers from distributing video without the authorization of the surveilled, and it is demonstrated how privacy can be enhanced while requiring no change to existing surveillance technology.
User-centric privacy awareness in video surveillance
TLDR
A model that allows users to directly interact with specially designed, trustworthy cameras and provide direct feedback about the tasks that are executed by the camera and how privacy-sensitive data is handled is presented.
Kalman Filter for Moving Object Tracking: Performance Analysis and Filter Design
This chapter presents Kalman filters for tracking moving objects and their efficient design strategy based on steady-state performance analysis. First, a dynamic/measurement model is defined for the
Connecting Pixels to Privacy and Utility: Automatic Redaction of Private Information in Images
TLDR
This work proposes the first sizable dataset of private images "in the wild" annotated with pixel and instance level labels across a broad range of privacy classes and presents the first model for automatic redaction of diverse private information.
Kalman Filtering for Sensor Fusion in a Human Tracking System
TLDR
In this chapter, the use of an inertial motion capture system for tracking full-body movements of the operator is described and a simple fusion algorithm of both tracking systems is presented.
The effects of filtered video on awareness and privacy
TLDR
The results suggest that the blur filter, and to a lesser extent the pixelize filter, have a level suitable for providing awareness information while safeguarding privacy.
On optimal ℓ∞ to ℓ∞ filtering
Graph Implementations for Nonsmooth Convex Programs
We describe graph implementations, a generic method for representing a convex function via its epigraph, described in a disciplined convex programming framework. This simple and natural idea allows a
Imagined Communities: Awareness, Information Sharing, and Privacy on the Facebook
TLDR
It is found that an individual's privacy concerns are only a weak predictor of his membership to the Facebook, and also privacy concerned individuals join the network and reveal great amounts of personal information.
...
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