Efficient search algorithm for block motion estimation

Jae Yong Kim, Sung Bong Yang

Research output: Contribution to journalConference article

4 Citations (Scopus)

Abstract

Many suboptimal motion vector search algorithms have been proposed because the full search algorithm, which is an optimal method, requires huge computational requirements. These algorithms find motion vectors simply from the center of the search window. In this paper we propose an efficient motion vector search algorithm (GLS), which exploits the global motion information obtained from the previous three frames and the local motion information regarding the motion vectors of the neighboring blocks of the current block in order to predict the initial search point. GLS searches for a motion vector from this initial search point, instead of the center of the search window, using either the diamond search algorithm (DS) or the unrestricted small diamond search algorithm (USDS) which performs its search always with a smaller diamond search pattern. USDS has the same search pattern as that of the last search step in DS. Experimental results show that GLS is a faster and more accurate motion vector search method than other suboptimal methods.

Original languageEnglish
Pages (from-to)100-109
Number of pages10
JournalIEEE Workshop on Signal Processing Systems, SiPS: Design and Implementation
Publication statusPublished - 1999 Dec 1

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Motion estimation
Diamonds

All Science Journal Classification (ASJC) codes

  • Engineering(all)

Cite this

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title = "Efficient search algorithm for block motion estimation",
abstract = "Many suboptimal motion vector search algorithms have been proposed because the full search algorithm, which is an optimal method, requires huge computational requirements. These algorithms find motion vectors simply from the center of the search window. In this paper we propose an efficient motion vector search algorithm (GLS), which exploits the global motion information obtained from the previous three frames and the local motion information regarding the motion vectors of the neighboring blocks of the current block in order to predict the initial search point. GLS searches for a motion vector from this initial search point, instead of the center of the search window, using either the diamond search algorithm (DS) or the unrestricted small diamond search algorithm (USDS) which performs its search always with a smaller diamond search pattern. USDS has the same search pattern as that of the last search step in DS. Experimental results show that GLS is a faster and more accurate motion vector search method than other suboptimal methods.",
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Efficient search algorithm for block motion estimation. / Kim, Jae Yong; Yang, Sung Bong.

In: IEEE Workshop on Signal Processing Systems, SiPS: Design and Implementation, 01.12.1999, p. 100-109.

Research output: Contribution to journalConference article

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AU - Kim, Jae Yong

AU - Yang, Sung Bong

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N2 - Many suboptimal motion vector search algorithms have been proposed because the full search algorithm, which is an optimal method, requires huge computational requirements. These algorithms find motion vectors simply from the center of the search window. In this paper we propose an efficient motion vector search algorithm (GLS), which exploits the global motion information obtained from the previous three frames and the local motion information regarding the motion vectors of the neighboring blocks of the current block in order to predict the initial search point. GLS searches for a motion vector from this initial search point, instead of the center of the search window, using either the diamond search algorithm (DS) or the unrestricted small diamond search algorithm (USDS) which performs its search always with a smaller diamond search pattern. USDS has the same search pattern as that of the last search step in DS. Experimental results show that GLS is a faster and more accurate motion vector search method than other suboptimal methods.

AB - Many suboptimal motion vector search algorithms have been proposed because the full search algorithm, which is an optimal method, requires huge computational requirements. These algorithms find motion vectors simply from the center of the search window. In this paper we propose an efficient motion vector search algorithm (GLS), which exploits the global motion information obtained from the previous three frames and the local motion information regarding the motion vectors of the neighboring blocks of the current block in order to predict the initial search point. GLS searches for a motion vector from this initial search point, instead of the center of the search window, using either the diamond search algorithm (DS) or the unrestricted small diamond search algorithm (USDS) which performs its search always with a smaller diamond search pattern. USDS has the same search pattern as that of the last search step in DS. Experimental results show that GLS is a faster and more accurate motion vector search method than other suboptimal methods.

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