• Journal of the Korean Society of Industry Convergence
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• v.25 no.4_2
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• pp.707-714
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• 2022

Versatile Video Coding (VVC) is the most recent video coding standard, which had been developed by Joint Video Expert Team (JVET). It can improve significant coding performance compared to the previous standard, namely High Efficiency Video Coding (HEVC). Although VVC can achieve the powerful coding performance, it requires the tremendous computational complexity of VVC encoder. Especially, affine motion compensation (AMC) was adopted the block-based 4-parameter or 6-parameter affine prediction to overcome the limit of translational motion model while VVC require the cost of higher encoding complexity. In this paper, we proposed the early termination of AMC that determines whether the affine motion estimation for AMC is performed or not. Experimental results showed that the proposed method reduced the encoding complexity of affine motion estimation (AME) up to 16% compared to the VVC Test Model 17 (VTM17).

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.750-755
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• 1998

Due to the temporal spatial correlation of the image sequence, the motion vector of a block is highly related to the motion vectors of its adjacent blocks in the same image frame. If we can obtain useful and enough information from the adjacent motion vectors, the total number of search points used to find the motion vector of the block may be reduced significantly. Using that idea, an efficient fuzzy prediction search (FPS) algorithm for block motion estimation is proposed in this paper. Based on the fuzzy inference process, the FPS can determine the motion vectors of image blocks quickly and correctly.

• The KIPS Transactions:PartB
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• v.10B no.7
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• pp.811-814
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• 2003

In this paper, we propose a fast block-matching motion estimation method using the cross pattern and the hexagonal pattern. For the block-matching motion estimation method, full search finds the best motion estimation, but it requires huge search time because it has to check every search point within the search window. The proposed method makes use of the fact that most of motion vectors lie near the center of block. The proposed method first uses the cross pattern to search near the center of block, and then uses the hexagonal pattern to search larger motion vectors. Experimental results show that our method is better than recently proposed search algorithms in terms of mean-square error performance and required search time.

• Journal of the Institute of Convergence Signal Processing
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• v.5 no.2
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• pp.96-105
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• 2004

The recovering 3D image from 2D requires the depth information for each picture element. The manual creation of those 3D models is time consuming and expensive. The goal in this paper is to estimate the relative depth information of every region from single view image with camera translation. The paper is based on the fact that the motion of every point within image which taken from camera translation depends on the depth. Motion vector using full-search motion estimation is compensated for camera rotation and zooming. We have developed a framework that estimates the average frame depth by analyzing motion vector and then calculates relative depth of region to average frame depth. Simulation results show that the depth of region belongs to a near or far object is consistent accord with relative depth that man recognizes.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.321-325
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• 2009

Sub-pel level motion estimation contributes to significant increase in R-D performance for H.264|MPEG 4 Part 10 AVC. However, several supplements, such as interpolation, block matching, and Hadamard transform which entails large computational complexity of encoding process, are essential to find best matching block in sub-pel level motion estimation and compensation. In this paper, a fast motion estimation scheme in sub-pel accuracy is proposed based on a parabolic model of SAD to avoid such computational complexity. In the proposed scheme, motion estimation (ME) is only performed in integer-pel levels and the following sub-pel level motion vectors are found from the parametric SAD model for which the model parameters are estimated from the SAD values obtained in the integer-pel levels. Fall-back check is performed to ensure the validity of the parabolic SAD model with the estimated parameters. The experiment result shows that the proposed scheme can reduce the motion estimation time up to about 30% of the total ME times in average with negligible amount of PSNR drops (0.14dB in maximum) and bit increments (2.54%in maximum).

• Journal of the Korean Society for Precision Engineering
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• v.32 no.4
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• pp.377-386
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• 2015

Joint force/torque estimation by inverse dynamics is a traditional tool in biomechanical studies. Conventionally for this, kinematic data of human body is obtained by motion capture cameras, of which the bulkiness and occlusion problem make it hard to capture a broad range of movement. As an alternative, inertial motion sensing using cheap and small inertial sensors has been studied recently. In this research, the performance of inertial motion sensing especially to calculate inverse dynamics is studied. Kinematic data from inertial motion sensors is used to calculate ground reaction force (GRF), which is compared to the force plate readings (ground truth) and additionally to the estimation result from optical method. The GRF estimation result showed high correlation and low normalized RMSE(R=0.93, normalized RMSE<0.02 of body weight), which performed even better than conventional optical method. This result guarantees enough accuracy of inertial motion sensing to be used in inverse dynamics analysis.

• Journal of Korea Multimedia Society
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• v.7 no.8
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• pp.1025-1034
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• 2004

This paper proposes an adaptive motion estimation algorithm using the temporal continuity of motion. We set up a squared global search region (GSR), which basically corresponds to the search region of FSA, and non-squared adaptive 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. Because motion estimation is only performed in the areas made by LSRs, we can estimate motion more correctly and reduce processing time. Experimental results show that the proposed method can enhance visual qualities with significant reductions of complexity by reducing search regions, when compared to the conventional methods.

• Journal of Korea Multimedia Society
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• v.4 no.5
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• pp.390-395
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• 2001

In this paper, we propose a fast warping prediction using bit-pattern for motion estimation. Because of the spatial dependency between motion vectors of neighboring node points carrying motion information, the optimization of motion search requires an iterative search. The computational load stemming from the iterative search is one of the major obstacles for practical usage of warping prediction. The motion estimation in the proposed algorithm measures whether the motion content of the area is or not, using bit-pattern. Warping prediction using the motion content of the area make the procedure of motion estimation efficient by eliminating an unnecessary searching. Experimental results show that the proposed algorithm can reduce more 75% iterative search while maintaining performances as close as the conventional warping prediction.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.1B
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• pp.167-174
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• 2000

The three-step search(TSS) algorithm, a simple and gradual motion estimation algorithm, has been widely used in some low bit-rate video compression. We propose a new fast block motion estimation algorithm using the characteristics of motion in search region. Most of motion vectors exist in the center region of search area, so the notion in that region is examined more closely than TSS in this paper. Also in a search step, motion vector is estimated in the local area which is not overlapped with the search area in previous step, considering the all possible direction of motion. Therefore, we get the better motion estimation and reduce computational time in compared with the conventional methods.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.2
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• pp.73-78
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• 2004

By modeling the block matching algorithm as a function of the correlation of image blocks, we derive search patterns for fast block matching motion estimation. The proposed approach provides an analytical support lot the diamond-shape search pattern, which is widely used in fast block matching algorithms. We also propose a new fast motion estimation algorithm using adaptive search patterns and statistical properties of the object displacement. In order to select an appropriate search pattern, we exploit the relationship between the motion vector and the block differences. By changing the search pattern adaptively, we improve motion prediction accuracy while reducing required computational complexity compared to other fast block matching algorithms.