A fast motion estimation using a three-dimensional reference motion vector

K. C. Lai; Siu Chung Wong

A fast motion estimation using a three-dimensional reference motion vector

K. C. Lai, Siu Chung Wong

The Hong Kong Polytechnic University

Research output: Journal article publication › Conference article › Academic research › peer-review

5 Citations (Scopus)

Abstract

Based on a study of the motion vector (MV) obtained by the Full Search algorithm among several test sequences, we found that the prediction process for motion estimation in many existing algorithms are not optimal. We optimize the prediction process by classifying the blocks into four different classes based on a newly proposed three-dimensional reference MV. Different search patterns and strategies are used for each class. The proposed algorithm can improve computation requirement as high as 43.9% than the diamond search algorithm.

Original language	English
Journal	ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume	4
Publication status	Published - 11 Jul 2002
Event	2002 IEEE International Conference on Acoustic, Speech, and Signal Processing - Orlando, FL, United States Duration: 13 May 2002 → 17 May 2002

ASJC Scopus subject areas

Software
Signal Processing
Electrical and Electronic Engineering

Cite this

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title = "A fast motion estimation using a three-dimensional reference motion vector",

abstract = "Based on a study of the motion vector (MV) obtained by the Full Search algorithm among several test sequences, we found that the prediction process for motion estimation in many existing algorithms are not optimal. We optimize the prediction process by classifying the blocks into four different classes based on a newly proposed three-dimensional reference MV. Different search patterns and strategies are used for each class. The proposed algorithm can improve computation requirement as high as 43.9% than the diamond search algorithm.",

author = "Lai, {K. C.} and Wong, {Siu Chung}",

year = "2002",

month = jul,

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language = "English",

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journal = "ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings",

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note = "2002 IEEE International Conference on Acoustic, Speech, and Signal Processing ; Conference date: 13-05-2002 Through 17-05-2002",

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T1 - A fast motion estimation using a three-dimensional reference motion vector

AU - Lai, K. C.

AU - Wong, Siu Chung

PY - 2002/7/11

Y1 - 2002/7/11

N2 - Based on a study of the motion vector (MV) obtained by the Full Search algorithm among several test sequences, we found that the prediction process for motion estimation in many existing algorithms are not optimal. We optimize the prediction process by classifying the blocks into four different classes based on a newly proposed three-dimensional reference MV. Different search patterns and strategies are used for each class. The proposed algorithm can improve computation requirement as high as 43.9% than the diamond search algorithm.

AB - Based on a study of the motion vector (MV) obtained by the Full Search algorithm among several test sequences, we found that the prediction process for motion estimation in many existing algorithms are not optimal. We optimize the prediction process by classifying the blocks into four different classes based on a newly proposed three-dimensional reference MV. Different search patterns and strategies are used for each class. The proposed algorithm can improve computation requirement as high as 43.9% than the diamond search algorithm.

UR - http://www.scopus.com/inward/record.url?scp=0036297806&partnerID=8YFLogxK

M3 - Conference article

SN - 1520-6149

VL - 4

JO - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

JF - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

T2 - 2002 IEEE International Conference on Acoustic, Speech, and Signal Processing

Y2 - 13 May 2002 through 17 May 2002

ER -

A fast motion estimation using a three-dimensional reference motion vector

Abstract

ASJC Scopus subject areas

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