Hilbert transform based workload estimation for low power surveillance video compression

Xin Jin, Satoshi Goto

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

In this paper, a workload estimation scheme is proposed for surveillance video encoding by using difference detection and Hilbert transform-based workload estimation model. Difference detection distributes the input video data according to their content similarity features and retrieves the encoding workload for the coded frames. Workload estimation model predicts the encoding workload for the following time slot using Hilbert transform and error control. Experimental results indicate that the proposed workload estimation model can provide accurate estimation results without performance hit to maintain the video encoding performance under a given performance constraint during power reduction.

Original languageEnglish
Title of host publicationProceedings - International Conference on Image Processing, ICIP
Pages4461-4464
Number of pages4
DOIs
Publication statusPublished - 2010
Event2010 17th IEEE International Conference on Image Processing, ICIP 2010 - Hong Kong
Duration: 2010 Sep 262010 Sep 29

Other

Other2010 17th IEEE International Conference on Image Processing, ICIP 2010
CityHong Kong
Period10/9/2610/9/29

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Keywords

  • Difference detection
  • DVFS
  • Encoding workload estimation
  • Hilbert transform

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing

Cite this

Jin, X., & Goto, S. (2010). Hilbert transform based workload estimation for low power surveillance video compression. In Proceedings - International Conference on Image Processing, ICIP (pp. 4461-4464). [5651500] https://doi.org/10.1109/ICIP.2010.5651500