• Journal of KIISE:Software and Applications
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• v.29 no.1_2
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• pp.98-113
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• 2002

In this paper, we present advanced algorithms to reduce the computations of block matching algorithms for motion estimation in video coding. Advanced multi-level successive elimination algorithms(AMSEA) are based on the Multi-level successive elimination algorithm(MSEA)[1]. The first algorithm is that when we calculate the sum of absolute difference (SAD) between the sum norms of sub-blocks in MSEA, we use the partial distortion elimination technique. By using the first algorithm, we can reduce the computations of MSEA further. In the second algorithm, we calculate SAD adaptively from large value to small value according to the absolute difference values between pixels of blocks. By using the second algorithm, the partial distortion elimination in SAD calculation can occur early. So, the computations of MSEA can be reduced. In the third algorithm, we can estimate the elimination level of MSEA. Accordingly, the computations of the MSEA related to the level lower than the estimated level can be reduced. The fourth algorithm is a very fast block matching algorithm with nearly 100% motion estimation accuracy. Experimental results show that AMSEA are very efficient algorithms for the estimation of motion vectors.

• The KIPS Transactions:PartB
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• v.17B no.1
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• pp.31-36
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• 2010

After the launch of MPEG-2, it is widely used in multimedia applications like a Digital-TV or a DVD. Then, After the launch of H.264 at 2004, it has been expected to replace MPEG-2 and services IPTV and DMB. As we have been used to MPEG-2 devices by this time, we can not access H.264 Broadcast with MPEG-2 device. So We propose a new approach to transcode H.264 video into MPEG-2 form which can facilitate to display H.264 video with MPEG-2 device. To reduce the quality loss by transcoding, we use CPDT(Cascaded Pixel Domain Transcoder) structure. And to minimize processing time, SKIP block, INTRA block and motion vectors obtain from decoding process is employed for transcoding. we use BMA(Boundary Matching Algorithm) to select only one from candidate motion vectors. Experimental results show a considerable improved PSNR with reduction in processing time compared with existing methods.

• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.501-504
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• 2005

블록 정합 기법(block matching algorithm, BMA) 중에서 가장 널리 알려진 3 단계 탐색(three-step search, 3SS) 알고리즘은 큰 움직임 추정에 적합하지만 고정된 탐색 점으로 인하여 작은 움직임 추정에는 계산 면에서 낭비가 심하고 탐색이 잘못될 경우가 대부분이다. 한편, 효율적인 3 단계 탐색(efficient three-step search, E3SS)은 중앙-편중된 움직임 추정을 작은 다이아몬드 탐색(small diamond search, SDS) 알고리즘으로 보완하여 예측성과 탐색 속도를 향상시킨 알고리즘이다. 본 논문에서는 탐색 초기 단계에서 탐색 점을 최적 배치하고 E3SS 의 SDS 알고리즘을 변형시킨 탐색 알고리즘을 제안한다. 실험 결과는 제안된 탐색 알고리즘이 E3SS 와 비교하여 평균 22% 정도 계산량을 감소시키면서도 MSE(Mean Square Error)의 성능 저하를 거의 보이지 않는 것으로 나타난다.

• 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.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.678-681
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• 2004

In this paper, efficient tracking of a moving object using optimal representative blocks is implemented by a mobile robot with a pan-tilt camera. The key idea comes from the fact that when the image size of moving object is shrunk in an image frame according to the distance between the camera of mobile robot and the moving object, the tracking performance of a moving object can be improved by changing the size of representative blocks according to the object image size. Motion estimation using Edge Detection(ED) and Block-Matching Algorithm(BMA) is often used in the case of moving object tracking by vision sensors. However these methods often miss the real-time vision data since these schemes suffer from the heavy computational load. In this paper, the optimal representative block that can reduce a lot of data to be computed, is defined and optimized by changing the size of representative block according to the size of object in the image frame to improve the tracking performance. The proposed algorithm is verified experimentally by using a two degree-of-freedom active camera mounted on a mobile robot.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.41.3-41
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• 2002

Motion estimation using Full-Search(FS) and Block-Matching Algorithm(BMA) is often used in the case of moving object tracking by vision sensors. However these methods often miss the real-time vision data because these schemes suffer the heavy computational load. When the image size of moving object is changed in an image frame according to the distance between the camera of mobile robot and the moving object, the tracking performance of a moving object may decline with these methods because of the shortage of active handling. In this paper, the variable-representative block that can reduce a lot of data computations, is defined and optimized by changing the size of representative block accor...

• The KIPS Transactions:PartB
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• v.8B no.5
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• pp.539-548
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• 2001

In this paper, we propose that fast tracking algorithm for moving object is separated from background, using partial boundary line information. After detecting boundary line from input image, we track moving object by using the algorithm which takes boundary line information as feature of moving object. we extract moving vector on the imput image which has environmental variation, using high-performance BMA, and we extract moving object on the basis of moving vector. Next, we extract boundary line on the moving object as an initial feature-vector generating step for the moving object. Among those boundary lines, we consider a part of the boundary line in every direction as feature vector. And then, as a step for the moving object, we extract moving vector from feature vector generated under the information of the boundary line of the moving object on the previous frame, and we perform tracking moving object from the current frame. As a result, we show that the proposed algorithm using feature vector generated by each directional boundary line is simple tracking operation cost compared with the previous active contour tracking algorithm that changes processing time by boundary line size of moving object. The simulation for proposed algorithm shows that BMA operation is reduced about 39% in real image and tracking error is less than 2 pixel when the size of feature vector is [$10{\times}5$] using the information of each direction boundary line. Also the proposed algorithm just needs 200 times of search operation bout processing cost is varies by the size of boundary line on the previous algorithm.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.12
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• pp.85-96
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• 1999

In a number of predictive video compression standards, the motion is compensated by the block-based motion compensation (BMC). The effective motion field used for the prediction by the BMC is obviously discontinuous since one motion vector is used for the entire macro-block. The usage of discontinuous motion field for the prediction causes the blocky artifacts and one obvious approach for eliminating such artifacts is to use a smoothed motion field. The optimal procedure will depend on the type of motion within the video. In this paper, several procedures for the motion vectors are considered. For any interpolation or approaches, however, the motion vectors as provided by the block matching algorithm(BMA) are no longer optimal. The optimum motion vectors(still one per macro-block) must minimize the of the displaced frame difference (DFD). We propose a unified algorithm that computes the optimum motion vectors to minimize the of the DFD using a conjugate gradient search. The proposed algorithm has been implemented and tested for the affine transformation based motion compensation (ATMC), the bilinear transformation based motion compensation (BTMC) and our own filtered motion compensation(FMC). The performance of these different approaches will be compared against the BMC.

• Proceedings of the Korean Information Science Society Conference
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• 2004.10c
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• pp.451-453
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• 2004

NTSS(New Three-Step Search Algorithm)는 대표적인 Fast BMA(Block Matching 시gorithm)인 TSS(Three-Step Search Algorithm)에 중앙 편향적(Center-Biased) 특성을 고려하여 향상시킨 방법이다. 그러나 NTSS는 움직임이 작은 영상인 경우에는 TSS보다 개선된 성능을 보여주지만, 움직임이 큰 영상에 대해서는 TSS와 큰 차이가 없으며 탐색영역이 커질수록 오히려 성능이 떨어지는 단점이 있다. 본 논문에서는 움직임 벡터의 특성에 맞는 탐색영역을 적용시킴으로써 탐색영역의 증가로 발생되는 NTSS의 단점을 보완하여 움직임이 큰 영상에 대해서도 향상된 성능을 갖는 방법을 제안한다. 제안된 방법을 적용 하였을때 움직임이 작은 영상에서는 기존의 방법과 동등한 결과를 얻었으며 움직임이 큰 영상에서는 최고 0.5db이상 성능이 개선되었다.

• 한국정보디스플레이학회:학술대회논문집
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• 2007.08a
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• pp.810-813
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• 2007

Recently, mobile video communication is getting more and more popular. Visual quality and computational complexity are primary factors affecting performance of video communication. Frame rate up-conversion (FRC) is necessary for achieving high visual quality in mobile projection displays. In this paper, a FRC method using motion compensation based on block matching algorithm (BMA) with adaptive block size is proposed. In order to improve the accuracy of the estimated motion vectors, the motion vector refinement technique is proposed. Experiment results indicate that the proposed technique exhibits better performance with lower hardware complexity compared to the conventional methods.