Fast, Robust Block Motion Estimation Using Simulated Annealing
Summary :
This paper presents a simulated annealing (SA)-based algorithm for fast and robust block motion estimation. To reduce computational complexity, the existing fast search algorithms move iteratively toward the winning point based only on a finite set of checking points in every stage. Despite the efficiency of these algorithms, the search process is easily trapped into local minima, especially for high activity image sequences. To overcome this difficulty, the new algorithm uses two sets of checking points in every search stage and invokes the SA to choose the appropriate one. The employment of the SA provides the search a mechanism of being able to move out of local minima so that the new algorithm is less susceptible to such a dilemma. In addition, two schemes are employed to further enhance the performance of the algorithm. First, a set of initial checking points which exploit high correlations among the motion vectors of the temporally and spatially adjacent blocks are used. Second, an alternating search strategy is addressed to visit more points without increasing computations. Simulation results show that the new algorithm offers superior performance with lower computational complexity compared to previous works in various scenarios.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E83-A No.1 pp.121-127
- Publication Date
- 2000/01/25
- Publicized
- Online ISSN
- DOI
- Type of Manuscript
- PAPER
- Category
- Digital Signal Processing
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Mon-Chau SHIE, Wen-Hsien FANG, Kuo-Jui HUNG, Feipei LAI, "Fast, Robust Block Motion Estimation Using Simulated Annealing" in IEICE TRANSACTIONS on Fundamentals,
vol. E83-A, no. 1, pp. 121-127, January 2000, doi: .
Abstract: This paper presents a simulated annealing (SA)-based algorithm for fast and robust block motion estimation. To reduce computational complexity, the existing fast search algorithms move iteratively toward the winning point based only on a finite set of checking points in every stage. Despite the efficiency of these algorithms, the search process is easily trapped into local minima, especially for high activity image sequences. To overcome this difficulty, the new algorithm uses two sets of checking points in every search stage and invokes the SA to choose the appropriate one. The employment of the SA provides the search a mechanism of being able to move out of local minima so that the new algorithm is less susceptible to such a dilemma. In addition, two schemes are employed to further enhance the performance of the algorithm. First, a set of initial checking points which exploit high correlations among the motion vectors of the temporally and spatially adjacent blocks are used. Second, an alternating search strategy is addressed to visit more points without increasing computations. Simulation results show that the new algorithm offers superior performance with lower computational complexity compared to previous works in various scenarios.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/e83-a_1_121/_p
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@ARTICLE{e83-a_1_121,
author={Mon-Chau SHIE, Wen-Hsien FANG, Kuo-Jui HUNG, Feipei LAI, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Fast, Robust Block Motion Estimation Using Simulated Annealing},
year={2000},
volume={E83-A},
number={1},
pages={121-127},
abstract={This paper presents a simulated annealing (SA)-based algorithm for fast and robust block motion estimation. To reduce computational complexity, the existing fast search algorithms move iteratively toward the winning point based only on a finite set of checking points in every stage. Despite the efficiency of these algorithms, the search process is easily trapped into local minima, especially for high activity image sequences. To overcome this difficulty, the new algorithm uses two sets of checking points in every search stage and invokes the SA to choose the appropriate one. The employment of the SA provides the search a mechanism of being able to move out of local minima so that the new algorithm is less susceptible to such a dilemma. In addition, two schemes are employed to further enhance the performance of the algorithm. First, a set of initial checking points which exploit high correlations among the motion vectors of the temporally and spatially adjacent blocks are used. Second, an alternating search strategy is addressed to visit more points without increasing computations. Simulation results show that the new algorithm offers superior performance with lower computational complexity compared to previous works in various scenarios.},
keywords={},
doi={},
ISSN={},
month={January},}
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TY - JOUR
TI - Fast, Robust Block Motion Estimation Using Simulated Annealing
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 121
EP - 127
AU - Mon-Chau SHIE
AU - Wen-Hsien FANG
AU - Kuo-Jui HUNG
AU - Feipei LAI
PY - 2000
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E83-A
IS - 1
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - January 2000
AB - This paper presents a simulated annealing (SA)-based algorithm for fast and robust block motion estimation. To reduce computational complexity, the existing fast search algorithms move iteratively toward the winning point based only on a finite set of checking points in every stage. Despite the efficiency of these algorithms, the search process is easily trapped into local minima, especially for high activity image sequences. To overcome this difficulty, the new algorithm uses two sets of checking points in every search stage and invokes the SA to choose the appropriate one. The employment of the SA provides the search a mechanism of being able to move out of local minima so that the new algorithm is less susceptible to such a dilemma. In addition, two schemes are employed to further enhance the performance of the algorithm. First, a set of initial checking points which exploit high correlations among the motion vectors of the temporally and spatially adjacent blocks are used. Second, an alternating search strategy is addressed to visit more points without increasing computations. Simulation results show that the new algorithm offers superior performance with lower computational complexity compared to previous works in various scenarios.
ER -
English
