Performance of optical flow techniques
International Journal of Computer Vision
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Kriging as a surrogate fitness landscape in evolutionary optimization
Artificial Intelligence for Engineering Design, Analysis and Manufacturing
A comprehensive survey of fitness approximation in evolutionary computation
Soft Computing - A Fusion of Foundations, Methodologies and Applications
Faster convergence by means of fitness estimation
Soft Computing - A Fusion of Foundations, Methodologies and Applications
Survey on Block Matching Motion Estimation Algorithms and Architectures with New Results
Journal of VLSI Signal Processing Systems
Lossy Strict Multilevel Successive Elimination Algorithm for Fast Motion Estimation
IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
Small-diamond-based search algorithm for fast block motion estimation
Image Communication
Computational Optimization and Applications
Block Matching Algorithm Based on Particle Swarm Optimization for Motion Estimation
ICESS '08 Proceedings of the 2008 International Conference on Embedded Software and Systems
Motion detection and object tracking with discrete leaky integrate-and-fire neurons
Applied Intelligence
New pixel-decimation patterns for block matching in motion estimation
Image Communication
Fast block matching using prediction and rejection criteria
Signal Processing
Generalizing surrogate-assisted evolutionary computation
IEEE Transactions on Evolutionary Computation
On-the-fly calibrating strategies for evolutionary algorithms
Information Sciences: an International Journal
Time series prediction evolving Voronoi regions
Applied Intelligence
Expert Systems with Applications: An International Journal
A neighborhood elimination approach for block matching in motion estimation
Image Communication
Computers and Industrial Engineering
A metamodel-assisted evolutionary algorithm for expensive optimization
Journal of Computational and Applied Mathematics
Pattern Recognition Letters
A memetic algorithm for the quadratic multiple container packing problem
Applied Intelligence
Circle Detection by Harmony Search Optimization
Journal of Intelligent and Robotic Systems
Accelerating evolutionary algorithms with Gaussian process fitness function models
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
A computational intelligence algorithm for expensive engineering optimization problems
Engineering Applications of Artificial Intelligence
VLSI implementation of genetic four-step search for block matching algorithm
IEEE Transactions on Consumer Electronics
A new diamond search algorithm for fast block-matching motion estimation
IEEE Transactions on Image Processing
Adaptive rood pattern search for fast block-matching motion estimation
IEEE Transactions on Image Processing
A novel four-step search algorithm for fast block motion estimation
IEEE Transactions on Circuits and Systems for Video Technology
A block-based gradient descent search algorithm for block motion estimation in video coding
IEEE Transactions on Circuits and Systems for Video Technology
A simple and efficient search algorithm for block-matching motion estimation
IEEE Transactions on Circuits and Systems for Video Technology
A lightweight genetic block-matching algorithm for video coding
IEEE Transactions on Circuits and Systems for Video Technology
Genetic motion search algorithm for video compression
IEEE Transactions on Circuits and Systems for Video Technology
Accuracy improvement and cost reduction of 3-step search block matching algorithm for video coding
IEEE Transactions on Circuits and Systems for Video Technology
A new three-step search algorithm for block motion estimation
IEEE Transactions on Circuits and Systems for Video Technology
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Motion estimation is one of the major problems in developing video coding applications. Among all motion estimation approaches, Block-matching (BM) algorithms are the most popular methods due to their effectiveness and simplicity for both software and hardware implementations. A BM approach assumes that the movement of pixels within a defined region of the current frame can be modeled as a translation of pixels contained in the previous frame. In this procedure, the motion vector is obtained by minimizing a certain matching metric that is produced for the current frame over a determined search window from the previous frame. Unfortunately, the evaluation of such matching measurement is computationally expensive and represents the most consuming operation in the BM process. Therefore, BM motion estimation can be viewed as an optimization problem whose goal is to find the best-matching block within a search space. The simplest available BM method is the Full Search Algorithm (FSA) which finds the most accurate motion vector through an exhaustive computation of all the elements of the search space. Recently, several fast BM algorithms have been proposed to reduce the search positions by calculating only a fixed subset of motion vectors despite lowering its accuracy. On the other hand, the Harmony Search (HS) algorithm is a population-based optimization method that is inspired by the music improvisation process in which a musician searches for harmony and continues to polish the pitches to obtain a better harmony. In this paper, a new BM algorithm that combines HS with a fitness approximation model is proposed. The approach uses motion vectors belonging to the search window as potential solutions. A fitness function evaluates the matching quality of each motion vector candidate. In order to save computational time, the approach incorporates a fitness calculation strategy to decide which motion vectors can be only estimated or actually evaluated. Guided by the values of such fitness calculation strategy, the set of motion vectors is evolved through HS operators until the best possible motion vector is identified. The proposed method has been compared to other BM algorithms in terms of velocity and coding quality. Experimental results demonstrate that the proposed algorithm exhibits the best balance between coding efficiency and computational complexity.