• 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 KIISE:Software and Applications
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• v.37 no.4
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• pp.305-310
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• 2010

In this paper, we propose a heuristic algorithm for motion correspondence based on a point series similarity. A point series is a sequence of points which are sorted in the ascending order of their x-coordinate values. The proposed algorithm clusters the points of a previous frame based on their local adjacency. For each group, we construct several potential point series by permuting the points in it, each of which is compared to the point series of the following frame in order to match the set of points through their similarity based on a proximity constraint. The longest common subsequence between two point series is used as global information to resolve the local ambiguity. Experimental results show an accuracy of more than 90% on two image sequences from the PETS 2009 and the CAVIAR data sets.

• ETRI Journal
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• v.34 no.3
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• pp.369-378
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• 2012

In this paper, we propose new adaptive search range motion estimation methods where the search ranges are constrained by the probabilities of motion vector differences and a search point sampling technique is applied to the constrained search ranges. Our new methods are based on our previous work, in which the search ranges were analytically determined by the probabilities. Since the proposed adaptive search range motion estimation methods effectively restrict the search ranges instead of search point sampling patterns, they provide a very flexible and hardware-friendly approach in motion estimation. The proposed methods were evaluated and tested with JM16.2 of the H.264/AVC video coding standard. Experiment results exhibit that with negligible degradation in PSNR, the proposed methods considerably reduce the computational complexity in comparison with the conventional methods. In particular, the combined method provides performance similar to that of the hybrid unsymmetrical-cross multi-hexagon-grid search method and outstanding merits in hardware implementation.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.672-676
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• 2004

In this paper, measuring system of 5 DOF motion errors are proposed using two capacitive type sensor, a straight edge and a laser interfoerometer. Yawing error and pitching error are measured using the laser interferometer, and rolling error is measured by the reversal method using a capacitive type sensor. Linear motion errors of horizontal and vertical direction are measured using the sequential two point method. In this case, influence of angular motion errors is compensated using the previously measured angular motion errors. In the horizontal direction, measuring accuracy is within 0.05 $\mu$m and 0.27 arcsec, and in the vertical direction, it is within 0.15 $\mu$m and 0.5 arcsec. From these results, it is confirmed that the proposed measureing system is very effective to the measurement of 5 DOF motion errors in the ultra precision feed tables.

• The KIPS Transactions:PartB
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• v.9B no.2
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• pp.199-204
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• 2002

Since motion estimation and motion compensation methods remove the redundant data to employ the temporal redundancy in images, it plays an important role in digital video compression. Because of its high computational complexity, however, it is difficult to apply to high-resolution applications in real time environments. If we have information about the motion of an image block before the motion estimation, the location of a better starting point for the search of an exact motion vector can be determined to expedite the searching process. In this paper, we present an adaptive motion estimation approach bated on temporal correlations of consecutive image frames that defines the search pattern and determines the location of the initial search point adaptively. Through experiments, compared with DS(Diamond Search) algorithm, the proposed algorithm is about 0.1∼0.5(dB) better than DS in terms of PSNR(Peak Signal to Noise Ratio) and improves as high as 50% compared with DS in terms of average number of search point per motion vector estimation.

• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.11
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• pp.1850-1856
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• 1989

For determining motion/structure of a 3-D rigid object from point correspondences over two perspective views, a linear algorithm was developed in Refs. 3 and 4. This algorithm fails when the 3-D points under observation satisfy certain geometrical constraints, as demonstrated in Refs. 7 and 8. In the present paper, we show that the linear algorithm can be resurrected in these degenerate cases by adding additional lower order polynomial constraints to original equations.

• Journal of the Korea Computer Industry Society
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• v.5 no.9
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• pp.987-992
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• 2004

There is the temporal correlation of the video sequence between the motion vector of current block and the motion vector of previous block. In this paper, we propose the improved diamond search pattern using an motion vector prediction candidate search point by the predicted motion information from the same block of the previous frame. Simulation results show that PSNR(Peak-to-Signal Noise Ratio) values are improves as high as high as 14~24% in terms of average number of search point per motion vector estimation and improved about 0.02~0.37dB on an average except the full search(FS) algorithm.

• International Journal of Highway Engineering
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• v.15 no.4
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• pp.127-133
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• 2013

PURPOSES : The impact performance of flexible barrier system such as structural response, vehicular motion and occupant safety vary depending on the impact point. Thus, to properly evaluate the performance of a flexible barrier system, impact should be made to a point which will lead to the worst possible results. This point is called the Critical Impact Point (CIP). This paper presents the way to determine the CIP for a SB2 class flexible barrier system which is consisted of Thrie-Beam rail and circular hollow tube post of 2m span. METHODS: Barrier VII simulations were made for impact points; Case 1 at a post, Case 2 at 1/3 span downstream from a post, Case 3 at middle of the span, Case 4 at 2/3 span downstream from a post. For the structural performance (deflections), impact simulation of 8000kg-65km/h-15degree was used, and for vehicle motion and occupant safety, simulation of 1300kg-80km/h-20degree impact was made and analysed. RESULTS: Case 1 gave the largest dynamic deflection of 75.72cm and also gave the largest snag value of 44.3cm. Occupant safety and exit angle of the vehicle after the impact were not sensitive to the impact point and were all below the allowable limit. CONCLUSIONS : For the SB2 class flexible barrier system's CIP can be regarded as a post which is sufficiently away from the end of Length of Need in order to avoid the end-effect of the barrier system. It can be more economic in the long run because the normal concrete pavement material is likely to cost more due to higher probability of maintenance and repair and higher social cost due to traffic accident, etc.

• The KIPS Transactions:PartB
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• v.11B no.3
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• pp.309-316
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• 2004

In this paper, we proposed the TDS(T-shape Diamond Search) based on the directions of above, below, left and right points to estimate the motion vector fast and more correctly in this method, we exploit the facts that most motion vectors are enclosed in a circular region with a radius of 2 fixels around search center(0,0). At first, the 4 points in the above, below, left and right around the search center is calculated to decide the point of the MBD(Minimum Block Distortion). And then w. above point of the MBD is checked to calculate the SAD. If the SAD of the above point is less than the previous MBD, this process is repeated. Otherwise, the right and left points of MBD are calculated to decide The points that have the MBD between right point and left point. Above processes are repeated to the predicted direction for motion estimation. Especially, if the motions of image are concentrated in the crossing directions, the points of other directions are omitted. As a result, we can estimate motion vectors fast. Experiments show that the speedup improvement of the proposed algorithm over Diamond Search algorithm(DS) and HEXgon Based Search(HEXBS) can be up to 38∼50％ while maintaining similar image Quality.

• Journal of the Korea Computer Graphics Society
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• v.9 no.3
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• pp.23-29
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• 2003

There is the temporal correlation of the video sequence between the motion vector of current block and the motion vector of the previous block. If we can obtain useful and enough information from the motion vector of the same coordinate block of the previous frame, the total number of search points used to find the motion vector of the current block may be reduced significantly. In this paper, we propose the block-matching motion estimation using an adaptive initial search point by the predicted motion information from the same block of the previous frame. And the first search point of the proposed algorithm is moved an initial point on the location of being possibility and the searching process after moving the first search point is processed according to the fast search pattern. Simulation results show that PSNR(Peak-to-Signal Noise Ratio) values are improved UP to the 1.05dB as depend on the image sequences and improved about 0.33~0.37dB on an average. Search times are reduced about 29~97% than the other fast search algorithms. Simulation results also show that the performance of the proposed scheme gives better subjective picture quality than the other fast search algorithms and is closer to that of the FS(Full Search) algorithm.