Hilbert transform based workload estimation for low power surveillance video compression

Xin Jin; Satoshi Goto

doi:10.1109/ICIP.2010.5651500

Hilbert transform based workload estimation for low power surveillance video compression

Xin Jin^*, Satoshi Goto

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference 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 language	English
Title of host publication	Proceedings - International Conference on Image Processing, ICIP
Pages	4461-4464
Number of pages	4
DOIs	https://doi.org/10.1109/ICIP.2010.5651500
Publication status	Published - 2010
Event	2010 17th IEEE International Conference on Image Processing, ICIP 2010 - Hong Kong Duration: 2010 Sept 26 → 2010 Sept 29

Other

Other	2010 17th IEEE International Conference on Image Processing, ICIP 2010
City	Hong Kong
Period	10/9/26 → 10/9/29

Keywords

Difference detection
DVFS
Encoding workload estimation
Hilbert transform

ASJC Scopus subject areas

Software
Computer Vision and Pattern Recognition
Signal Processing

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10.1109/ICIP.2010.5651500

Cite this

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title = "Hilbert transform based workload estimation for low power surveillance video compression",

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.",

keywords = "Difference detection, DVFS, Encoding workload estimation, Hilbert transform",

author = "Xin Jin and Satoshi Goto",

year = "2010",

doi = "10.1109/ICIP.2010.5651500",

language = "English",

isbn = "9781424479948",

pages = "4461--4464",

booktitle = "Proceedings - International Conference on Image Processing, ICIP",

note = "2010 17th IEEE International Conference on Image Processing, ICIP 2010 ; Conference date: 26-09-2010 Through 29-09-2010",

}

TY - GEN

T1 - Hilbert transform based workload estimation for low power surveillance video compression

AU - Jin, Xin

AU - Goto, Satoshi

PY - 2010

Y1 - 2010

N2 - 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.

AB - 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.

KW - Difference detection

KW - DVFS

KW - Encoding workload estimation

KW - Hilbert transform

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U2 - 10.1109/ICIP.2010.5651500

DO - 10.1109/ICIP.2010.5651500

M3 - Conference contribution

AN - SCOPUS:78651096321

SN - 9781424479948

SP - 4461

EP - 4464

BT - Proceedings - International Conference on Image Processing, ICIP

T2 - 2010 17th IEEE International Conference on Image Processing, ICIP 2010

Y2 - 26 September 2010 through 29 September 2010

ER -

Hilbert transform based workload estimation for low power surveillance video compression

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Keywords

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