• 전자공학회논문지B
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• 제30B권4호
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• pp.104-115
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• 1993

The motion compensated coding (MCC) technique, which exploits the temporal redundancies in the moving images with the motion estimation technique,is one of the most popular techniques currently used. Recently, a variable block size(VBS) motion estimation scheme has been utilized to improve the performance of the motion compensted coding. This scheme allows large blocks to the used when smaller blocks provide little gain, saving rates for areas containing more complex motion. Hence, a new VBS motion estimation scheme with a hierarchical structure is proposed in this paper, in order to combine the motion vector coding technique efficiently. Topmost level motion vector, which is obtained by the gain/cost motion estimation technique with selective motion prediction method, is always transmitted. Thus, the hierarchical VBS motion estimation scheme can efficiently exploit the redundancies among neighboring motion vectors, providing an efficient motion vector encoding scheme. Also, a restricted search with respect to the topmost level motion vector enables more flexible and efficient motion estimation for the remaining lower level blocks. Computer simulations on the high resolution image sequence show that, the VBS motion estimation scheme provides a performance improvement of 0.6~0.7 dB, in terms of PSNR, compared to the fixed block size motion estimation scheme.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2003년도 하계종합학술대회 논문집 II
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• pp.851-854
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• 2003

The low power motion estimation for MPEG-4 is a soft-core for hardwired motion estimation block in MPEG-4. This motion estimation is modified by 10 difference mode. So, this motion estimation decrease a power consumption compare conventional step search. This modified 4SS Low power Motion Estimation has been tested and verified to be valid for implementation of FPGA. The average PSNR between the original image and the motion-compensated image is 28.25dB. And Power consumption is 26mW.

• 한국멀티미디어학회논문지
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• 제17권8호
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• pp.915-922
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• 2014

We propose an adaptive zoom motion estimation method where a picture is divided into two areas based on the distance information with a depth camera : the one is object area and the other is background area. In the proposed method, the zoom motion is only applied to the object area except the background area. Further, the block size of motion estimation for the object area is set to smaller than that of background area. This adaptive zoom motion estimation method can be reduced at the complexity of motion estimation and can be improved at the motion estimation performance by reducing the block size of the object area in comparison with the conventional zoom motion estimation method. Based on the simulation results, the proposed method is compared with the conventional methods in terms of motion estimation accuracy and computational complexity.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 2009년도 IWAIT
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• pp.408-412
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• 2009

In this paper, a new efficient algorithm for global motion estimation is proposed. This algorithm uses a previous 4-parameter model based global motion estimation algorithm and M-estimator for improving the accuracy and robustness of the estimate. The first algorithm uses the block based motion vector fields and which generates a coarse global motion parameters. And second algorithm is M-estimator technique for getting precise global motion parameters. This technique does not increase the computational complexity significantly, while providing good results in terms of estimation accuracy. In this work, an initial estimation for the global motion parameters is obtained using simple 4-parameter global motion estimation approach. The parameters are then refined using M-estimator technique. This combined algorithm shows significant reduction in mean compensation error and shows performance improvement over simple 4-parameter global motion estimation approach.

• 한국통신학회논문지
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• 제21권4호
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• pp.807-821
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• 1996

In this paper, we proposed a nonlinear hierarchical mtion estimation method. Generally, the conventional hierarchical motion estimation methods have been proposed for fast convergence and detection of large motions. But they have a common drawback that large error in motion estimation is propapated across motion discontinuities. This artifiact is due to the constriaint of motion continuity and the linear interpolation of motion vectors between hierarchical levels. In this paper, we propose an effective hierarchical motion estimation mechod that is robust to motion discontinuities. The proposed algorithm is based on the decomposition of the functional domain for optimizing the intra-level motion estimation functional. Also, we propose an inter-level nonlinear motion estimation equation rather than using the conventional linearprojection scheme of motion field. computer simulations with several test sequences show tht the proposed algorithm performs better than several conventional methods.

• 한국멀티미디어학회논문지
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• 제20권11호
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• pp.1842-1848
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• 2017

Recently, user motion estimation methods using various wearable devices have been actively studied. In this paper, we propose a motion estimation system using Myo, which is one of the wearable devices, using two Myo and their dependency relations. The estimated motion is used as a command for remotely controlling the robot. Myo's Orientation and EMG signals are used for motion estimation. These two type data sets are used complementarily to increase the accuracy of motion estimation. We design and implement the system according to the proposed method and analyze the results through experiments. As a result of comparison with previous studies, the accuracy of motion estimation can be improved by about 12.3%.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 하계종합학술대회 논문집(4)
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• pp.287-290
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• 2002

The block matching algorithm motion estimation is a soft-core for hardwired motion estimation block in MPEG-2, H.261 encoder. This motion estimation has been tested and verified to be valid for implementation of FPGA. Efficiency performance of the synthesized motion estimation was up to 89%, and the average PSNR between the original image and the motion-compensated image is 38dB.

• ETRI Journal
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• 제37권4호
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• pp.766-771
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• 2015

Robust motion estimation for human-computer interactions played an important role in a novel method of interaction with electronic devices. Existing pose estimation using a monocular camera employs either ego-motion or exo-motion, both of which are not sufficiently accurate for estimating fine motion due to the motion ambiguity of rotation and translation. This paper presents a hybrid vision-based pose estimation method for fine-motion estimation that is specifically capable of extracting human body motion accurately. The method uses an ego-camera attached to a point of interest and exo-cameras located in the immediate surroundings of the point of interest. The exo-cameras can easily track the exact position of the point of interest by triangulation. Once the position is given, the ego-camera can accurately obtain the point of interest's orientation. In this way, any ambiguity between rotation and translation is eliminated and the exact motion of a target point (that is, ego-camera) can then be obtained. The proposed method is expected to provide a practical solution for robustly estimating fine motion in a non-contact manner, such as in interactive games that are designed for special purposes (for example, remote rehabilitation care systems).

• 한국통신학회논문지
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• 제29권1C호
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• pp.149-156
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• 2004

본 논문에서는 저전력 멀티미디어 통신을 위한 새로운 전력 의식 움직임 추정 기법을 제안한다. 동영상 압축 기법에서 가장 많은 전력을 소모하는 것은 움직임 추정 기법인데, 일반적으로 성능이 우수한 기법일수록 전력 소모도 높다. 제안하는 움직임 추정 기법에서는 서로 다른 전력 소모와 성능을 가지는 여러 개의 움직임 추정 기법 중에서 연산량과 전력 소모의 절충을 고려하여 최적의 움직임 추정 기법을 실행 중에 적응적으로 선택한다. 제안하는 움직임 추정 기법은 현재 사용되는 대부분의 움직임 추정 기법에 쉽게 적용될 수 있으며, 추가되는 연산량이나 하드웨어 부담도 거의 없다. 모의 실험 결과에 따르면 제안하는 움직임 추정 기법은 기존의 움직임 추정 기법에 비교하였을 때 동일한 성능에서 전력 소모를 1/15.7~1/5.6으로 줄일 수 있었다.

• 방송공학회논문지
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• 제20권6호
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• pp.880-887
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• 2015

본 논문은 EBME(Extended Bilateral Motion Estimation) 알고리듬에서 동일한 움직임 벡터들의 방향과 크기를 고려한 알고리듬을 제안하였다. EBME는 BME(Bilateral Motion Estimation)보다 높은 연산량을 요구하기 때문에 프레임 내의 x, y방향 각각의 평균 움직임 벡터크기를 이용하여 동적프레임과 정적프레임을 판단하고, EBME 수행여부를 판단하여 연산량을 줄인다. 또한 동일한 움직임 벡터들의 방향과 크기를 비교하여 MVS(Motion Vector Smoothing)단계 수행여부를 판단함으로써 연산량을 줄인다. 제안하는 알고리듬을 적용한 실험 결과 기존의 EBME 알고리듬에 비해 수행시간은 단축되고 PSNR(Peak Signal to Noise Ratio)은 향상 되었다.