• Journal of the Korea Society of Computer and Information
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• v.11 no.4 s.42
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• pp.77-85
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• 2006

There is the spatial correlation of the video sequence between the motion vector of current blocks. In this paper, we propose the enhanced fast block matching algorithm using the spatial correlation of the video sequence and the center-biased properly of motion vectors. The proposed algorithm determines an exact motion vector using the predicted motion vector from the adjacent macro blocks of the current frame and the Cross-Hexagonal search pattern. From the of experimental results, we can see that our proposed algorithm outperforms both the prediction search algorithm (NNS) and the fast block matching algorithm (CHS) in terms of the search speed and the coded video's quality. Using our algorithm, we can improve the search speed by up to $0.1{\sim}38%$ and also diminish the PSNR (Peak Signal Noise Ratio) by at nst $0.05{\sim}2.5dB$, thereby improving the video qualify.

• Proceedings of the IEEK Conference
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• 2000.07a
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• pp.7-10
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• 2000

Fast block motion estimation technique is proposed to reduce the computational complexity in video coding. In the conventional methods the size of search region is fixed. For small motion regions like background the small size of sea of search region is enough to find a block motion. But for active motion regions the large size of search region is preferred to figure out the accurate motion vector. Therefore, it is reasonable that a block motion is estimated in the variable search region (both the size and the position of it). That is to say, the search region varies according to the predicted motion characteristics of a block. The block motion in video frames has temporal continuity and then the search region of a current block is predicted using the block motion of previous blocks. The computational complexity of the proposed technique is significantly reduced with a good picture quality compared to the conventional methods.

• ETRI Journal
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• v.29 no.6
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• pp.826-828
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• 2007

Efficient downscaling in a transcoder is important when the output should be converted to a lower resolution video. In this letter, we suggest an efficient algorithm for transcoding from MPEG-4 SP (with simple profile) to H.264/AVC with spatial downscaling. First, target image blocks are classified into monotonous, complex, and very complex regions for fast mode decision. Second, adaptive search ranges are applied to these image classes for fast motion estimation in an H.264/AVC encoder with predicted motion vectors. Simulation results show that our transcoder considerably reduces transcoding time while video quality is kept almost optimal.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.785-786
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• 2008

In this paper, we propose a fast Motion Estimation (ME) algorithm for low computational complexity based on spatial correlations. The proposed algorithm uses the motion vector of neighboring blocks, to decide the location of initial searching point. The number of searching point decreases by changing the location of initial searching point. Experimental results show that the proposed algorithm reduces searching points about $7{\sim}13%$ and increases PSNR about $0.1{\sim}0.5$(dB) compared with conventional algorithm.

• Journal of the Korea Society of Computer and Information
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• v.22 no.7
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• pp.47-54
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• 2017

Recently, correlation filter based trackers have shown excellent tracking performance and computational efficiency. In order to enhance tracking performance in the correlation filter based tracker, search area which is image patch for finding target must include target. In this paper, two methods to discriminatively represent target in the search area are proposed. Firstly, search area location is estimated using pyramidal Lucas-Kanade algorithm. By estimating search area location before filtering, fast motion target can be included in the search area. Secondly, we investigate multi-channel Local Edge Pattern(LEP) which is insensitive to illumination and noise variation. Qualitative and quantitative experiments are performed with eight dataset, which includes ground truth. In comparison with method without search area estimation, our approach retain tracking for the fast motion target. Additionally, the proposed multi-channel LEP improves discriminative performance compare to existing features.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.3
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• pp.74-79
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• 2008

In an H.264/AVC video encoder, the motion estimation at fractional pixel accuracy improves a coding efficiency and image quality. However, it requires additional computation overheads for fractional search and interpolation, and thus, reducing the computation complexity of fractional search becomes more important. This paper proposes fast fractional search algorithms by combining the SASR(Simplified Adaptive Search Range) and the MSDSP(Mixed Small Diamond Search Pattern) with the predicted fractional motion vector. Compared with the full search and the prediction-based directional fractional pixel search, the proposed algorithms can reduce up to 93.2% and 81% of fractional search points, respectively with the maximum PSNR lost less than 0.04dB. Therefore, the proposed fast search algorithms are quite suitable for mobile applications requiring low power and complexity.

• Journal of Korea Multimedia Society
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• v.6 no.7
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• pp.1121-1130
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• 2003

This paper proposes a new motion estimation algorithm using the temporal continuity of motion. We set up a wide global search region (GSR), which basically corresponds to the search region of FSA, and local search regions (LSRs), the positions for which are predicted by the motion vectors of the temporal neighbor blocks, are constructed in the GSR. The previous frame blocks that possibly have effects on the current block are to be the temporal neighbor blocks. Then Motion estimation is only performed in the areas made by LSRs. Experimental results show that the proposed method can maintain visual qualifies with significant reductions of complexity by reducing search regions, when compared to the conventional FSA.

• Proceedings of the IEEK Conference
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• 2000.11d
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• pp.57-60
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• 2000

This paper presents a new adaptive fast motion estimation algorithm along with its architecture. The conventional algorithm such as full - search algorithm, three step algorithm have some disadvantages which are related to the amount of computation, the quality of image and the implementation of hardware, the proposed algorithm uses spatial correlation and a slope of motion vector in order to reduce the amount of computation and preserve good image quality, The proposed algorithm is better than the conventional Block Matching Algorithm(BMA) with regard to the amount of computation and image quality. Also, we propose an efficient at chitecture to implement the proposed algorithm. It is suitable for real time processing application.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.6
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• pp.35-48
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• 1993

In this paper, a hierarchical motion vector estimation algorithm using pyramidal structure is proposed. Using a smaller measurement window at each level of a pyramid than that of the conventional scheme, the proposed algorithm, based on the TSS(three step search), reduces the computational complexity greatly with its performance comparable to that of the TSS. By increasing the number of cnadidate motion vectors which are to be used as the initial search points for motion vector estimation at the next level, the performance improves further. Then the computational complexity of the proposed hierarchical algorithm depends on the number of candidate motion vectors, with its PSNR (peak signal to noise ratio) ranging between those of the TSS and the full search method. The simulation results with two different block sizes and various test sequences are given and its hardware implementation is also sketched.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1996.06b
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• pp.41-44
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• 1996

A new three step hierarchical search algorithm for motion estimation is proposed. The proposed algorithm exploits the motion correlation of spatially neighboring blocks and the motion continuity of temporally neighboring blocks to alleviate the local minimum problem in the first step of the three step hierarchical search algorithm (3SHS). Simulation results show that the proposed scheme achieves significant improvements in both estimation accuracy and performance reliability compared with the existing fast block matching algorithm including 3SHS, while maintaining almost the same computational complexity as 3SHS. The proposed scheme also possesses the regularity and simplicity of hardware-oriented features.