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Privacy Preserving Real-Time Video Stream Change Detection Based on the Orthogonal Tensor Decomposition Models

  • Bogusław CyganekEmail author
Conference paper
  • 35 Downloads
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 385)

Abstract

In this paper the video change detection method that allows for data privacy protection is proposed. Signal change detection is based on the tensor models constructed in the orthogonal tensor subspaces. Tensor methods allow for processing of any kind of multi-dimensional signals since computation of special features is not required. The proposed signal encoding method makes that person identification in the processed signal is very difficult or impossible for the unauthorized personnel. It is demonstrated that despite the input being distorted for encryption, the proposed tensor based method can still correctly identify video shots in real-time. Compared with the non-distorted signals, the obtained accuracy is only slightly lower, at the same time providing data privacy.

Keywords

Data privacy Image encryption Video analysis Tensor models HOSVD Real-time algorithms 

Notes

Acknowledgement

This work was supported by the Polish National Science Center NCN under the grant no. 2016/21/B/ST6/01461.

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.AGH University of Science and TechnologyKrakówPoland

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