Kwanghyun Won, Jungyoup Yang, Byeungwoo Jeon · 2009
The H.264/AVC standard employs the predictive motion vector coding technique using the median predictor of spatially neighboring three motion vectors. Although the median is effective in reducing redundancy, it is not always optimal in minimizing bits. To solve the matter, a new motion vector coding scheme, known as, MV competition in which decoder is signaled on the selected optimal PMV, has been reported. Though it can use the optimal PMV(Predicted Motion Vector), the bits consumed to indicating the optimal PMV to the decoder increases bit-rate. In this paper, we propose a new motion vector coding scheme that allows usage of an optimal PMV without consuming additional bits to inform the choice of PMV to decoder. Simulation results show that the proposed method gains in BDBR by 3.22% on average, and in BDPSNR by 0.13 dB compared to the H.264/AVC.
Cited by 4
Data Archiving and Networked Services (DANS) · 2008
In a method for determining motion vectors from image data for blocks or objects of an image taken from an image sequence a block B(X) or object of pixels is divided ( 33 ) in two or more groups (Ga, Gb) within the block B(X) or object a motion vector (Da, Db) are assigned to the block (B(X)) and applied to the pixels of the respective groups (Ga, Gb) within the block.
Cited by 0Open access
Haan, G Gerard de · TU/e Research Portal (Eindhoven University of Technology) · 2008
In a method for determining motion vectors from image data for blocks or objects of an image taken from an image sequence a block B(X) or object of pixels is divided ( 33 ) in two or more groups (Ga, Gb) within the block B(X) or object a motion vector (Da, Db) are assigned to the block (B(X)) and applied to the pixels of the respective groups (Ga, Gb) within the block.
Cited by 0
Data Archiving and Networked Services (DANS) · 2009
A selector (502) for selecting a background motion vector for a pixel in an occlusion region of an image, from a set of motion vectors being computed for the image, comprises: computing means (510) for computing a model-based motion vector for the pixel on basis of a motion model being determined on basis of a part of (402-436) a motion vector field (400) of the image; comparing means (511) for comparing the model-based motion vector with each of the motion vectors of the set of motion vectors; and selecting means (512) for selecting a particular motion vector of the set of motion vectors on basis of the comparing and for assigning the particular motion vector as the background motion vector.
Cited by 0
Wittebrood, RB, Haan, G Gerard de, Lodder, R · TU/e Research Portal (Eindhoven University of Technology) · 2009
A selector (502) for selecting a background motion vector for a pixel in an occlusion region of an image, from a set of motion vectors being computed for the image, comprises: computing means (510) for computing a model-based motion vector for the pixel on basis of a motion model being determined on basis of a part of (402-436) a motion vector field (400) of the image; comparing means (511) for comparing the model-based motion vector with each of the motion vectors of the set of motion vectors; and selecting means (512) for selecting a particular motion vector of the set of motion vectors on basis of the comparing and for assigning the particular motion vector as the background motion vector.
Cited by 0
Rey R. Furner, R.W. Christiansen, Douglas M. Chabries · 2005
Two algorithms combining vector quantization with motion compensation for data reduction are presented. The vector quantization technique used in the algorithms is a mean residual vector quantizer (MRVQ) with 8-bit mean, and the motion compensation technique is a simple block matching algorithm. Both VQ and motion compensation are based on squared error performance criterion. The algorithms are tested on USC data base sequences and distortions plotted. A comparison is made between motion compensated vector quantization and conventional VQ.
Cited by 3
Myung-Hun Jang, Chan-Won Seo, Jong-Ki Han · Journal of Broadcast Engineering · 2012
MPEG-2, MPEG-4와 같은 기존의 비디오 코덱에서는 인터 예측을 수행할 때 고정된 해상도의 움직임 벡터를 사용한다. 그러나 KTA 참조 소프트웨어에서는 움직임 벡터의 해상도를 슬라이스 단위로 선택하여 사용할 수 있는 기능을 지원한다. 그러나 선택된 하나의 움직임 벡터 해상도를 슬라이스 전체에 일괄적으로 적용하기 때문에 영상의 국지적인 특성을 반영하는데 어려움이 있다. 본 논문에서는 탐색 구간에 따라 적응적으로 움직임 벡터의 해상도를 결정하는 방법을 제안한다. 움직임 벡터의 탐색 영역을 움직임 벡터가 예측 움직임 벡터로부터 떨어진 거리에 따라 다수개의 구간으로 분할하고, 각 구간에 대하여 하나의 움직임 벡터 해상도를 할당하여 움직임 예측에 적용한다. 따라서 제안하는 방법의 부호화 효율은 각 구간을 분할하는 Threshold와 움직임 벡터를 부호화하는 엔트로피 코딩 방법에 영향을 받는다. HEVC의 참조 소프트웨어인 HM3.0을 이용하여 실험한 결과, Random Access 부호화 구조에서는 평균적으로 약 0.9%의 성능 향상을 얻을 수 있었으며, Low Delay 부호화 구조에 B picture를 적용한 경우는 약 0.6%, P picture를 적용한 경우에서는 약 2.7%의 평균 발생 비트량 감소를 확인할 수 있었다. In most conventional video codecs, such as MPEG-2 and MPEG-4, inter coding is performed with the fixed motion vector resolution. When KTA software was developed, resolution for MVs can be selected in each slice. Although KTA codec uses a variety of resolutions for ME, the selected resolution is applied over the entire pixels in the slice and the statistical property of the local area is not considered. In this paper, we propose an adaptive decision scheme for motion vector resolution which depends on region, where MV search area is divided to multiple regions according to the distance from PMV. In each region, the assigned resolution is used to estimate MV. Each region supports different resolution for ME from other regions. The efficiency of the proposed scheme is affected from threshold values to divide the search area and the entropy coding method to encode the estimated MV. Simulation results with HM3.0 which is the reference software of HEVC show that the proposed scheme provides bit rate gains of 0.9%, 0.6%, and 2.9% in Random Access, Low Delay with B picture, and Low Delay with P picture structures, respectively.
Cited by 0Open access
Hai Bing Yin, Xiang Fang, Hua Yang et al. · 2006
This paper proposes a new motion vector (MV) smoothing algorithm to track the real motion in image sequences for MPEG video encoders. First, a pre-checking algorithm is employed to eliminate wrong motion vectors and preserve all possible motion vectors. For each block considered, the motion similarity between the neighboring blocks and the number of candidate motion vectors are jointly exploited to adaptively grow the filtering support, which is supposed to have homogeneous motion and sufficient spatial gradient. Then, all candidate motion vectors are checked within the filtering support using a new motion smoothness-constrained matching criteria. The simulation results show that the proposed algorithm can efficiently track the real motion resulting in smooth motion vector field (MVF).
Cited by 15
I.R. Ismaeil, Alen Docef, F. Kossentini et al. · 1999
Summary form only given. This paper presents a motion estimation technique for the coding of video sequences that is based on long-term temporal prediction. The motion vector of a moving object is tracked from one frame to another using a projection method. The traced motion vector is used as a starting point for the motion estimation search algorithm. The motion estimation algorithm used is based on an optimum fast block matching algorithm. Combinations of both spatial and temporal prediction are also used to obtain a more accurate estimate of the motion vector of the current macroblock. An inaccurately predicted motion vector can have a significant negative impact on the motion estimation algorithm. It can force the search algorithm to be trapped in a local minimum, or to spend unnecessary computations to find the optimum motion vector. The accuracy of the predicted motion vector is estimated using a reliability measure that allows the motion search algorithm to decide whether to use temporal motion vector predictor, spatial motion vector predictor, or both. As a reliability measure we used the mean squared error between the traced motion vectors in the current frame and in the previous frame. The reliability measure increases if the motion vector belongs to a moving object with constant speed. If the reliability measure is smaller than a certain threshold, then we abandon the temporal prediction and use spatial prediction. If both prediction methods fail, we abandon the fast motion search and perform full-search motion estimation in the low-resolution images. The experimental results show that long-term prediction reduces the number of computations performed by the motion search algorithm by up to 20%, while obtaining essentially the same quality.
Cited by 8
Dong-Il Chang, Jun Seok Song, Seung Jun Lee et al. · 2002
Motion vector field is generally encoded by using an intraframe differential coding, that is, the well known DPCM approach. An interframe differential coding might be an alternative when the motion vector field is not spatially smooth enough. In this paper, we propose a multistage interframe differential coding approach. In addition to the temporal dependencies between the motion vector fields, temporal dependencies between residual vector fields of consecutive stages are also exploited in this approach. An accumulated average for generating the compensation vector field is also proposed in this paper. Experimental results have shown that the proposed approach is more suitable for real applications where various characteristics of motion fields might exist.
Cited by 0
Kwanghyun Won, Jungyoup Yang, Dae-Yun Park et al. · Journal of Broadcast Engineering · 2011
본 논문은 영상의 움직임 특성을 참조하여 움직임 벡터 수평-수직 성분중 하나를 최적의 예측 움직임 벡터 성분으로 선택하여 사용할 수 있는 개선된 교차 움직임벡터 부호화 방법을 제시한다. 제안방법은 부-복호화를 수행할 움직임 벡터 성분의 순서를 복호화기에 알리는 신호비트를 별도로 보낼 필요 없이, 시공간적 움직임필드의 특성을 참조하여 적절한 움직임벡터 성분 예측치를 적응적으로 사용할 수 있다. 기존 H.264/AVC 방법과 비교한 실험 결과, 평균적으로 전체 비트량을 약 1.99% (최대 8.71%) 감소시킬 수 있음을 보여준다. This paper proposes an improved design of an interleaved motion vector coding scheme with flexibility in predictive motion vector component by exploiting motion characteristics. It can use component-wise adaptive motion vector predictor based on the utility of spatial and temporal motion field without any signaling bit for indicating decoder of the selected predictive motion vector component. Experiment with test video data shows about 1.99% (max 8.71%) bit rate reduction compared to the conventional H.264/AVC method.
Cited by 0Open access
Data Archiving and Networked Services (DANS) · 2006
Cited by 0
Olivier A. Bauchau, Jou-Young Choi · Nonlinear Dynamics · 2003
Cited by 39
Kwanghyun Won, Jungyoup Yang, Byeungwoo Jeon · 2011
In this paper, an interleaved motion vector coding is proposed which supports flexible coding order of motion vector components according to directional property of vertical and horizontal components in motion vector field. It requires no additional information for adaptively selecting the coding order.
Cited by 0
Chia‐Hung Yeh, Chih‐Jung Kuo · 2001
There is a need to downscale the video (from image size to ) prior to transmission due to bandwidth limitation on the cannel. The conventional method for downscaling the video sequence is to decompress the video bitstream and then reencode it again at video server. This process is computationally intensive because of the motion estimation required during the reencoding process. In this paper, we proposed a polynomial motion-vector resampling (PMVR) algorithm to compute motion vectors for the downscaled video sequence in compressed domain. The proposed approach leads to significant computational saving compared with the conventional spatial domain approach. Simulation results suggest that the proposed method is effective for video downscaling.
Cited by 2
Rasmus Larsen · Technical University of Denmark, DTU Orbit (Technical University of Denmark, DTU) · 1993
This paper presents an approach to the estimation of 2-D motion vector fields from time varying image sequences. We use a piecewise smooth model based on coupled vector/binary Markov random fields. We find the maximum a posteriori solution by simulated annealing. The algorithm generate sample fields by means of stochastic relaxation implemented via the Gibbs sampler. 1
Cited by 1Open access
David Suter · 1994
Many formulations of visual reconstruction problems (e.g., optic flow, shape from shading, biomedical motion estimation from CT data) involve the recovery of a vector field. Often the solution is characterized via a generalized spline or regularization formulation using a smoothness constraint. This paper introduces a decomposition of the smoothness constraint into two parts: one related to the divergence of the vector field and one related to the curl or vorticity. This allows one to "tune" the smoothness to the properties of the data. One can, for example, use a high weighting on the smoothness imposed upon the curl in order to preserve the divergent parts of the field. For a particular spline within the family introduced by this decomposition process, we derive an exact solution and demonstrate the approach on examples. 1 Introduction This papers addresses some aspects of the general problem of the reconstruction of a vector field. This general problem can arise in applications req...
Cited by 0
Rare & Special e-Zone (The Hong Kong University of Science and Technology) · 2003
Cited by 0
F. Ahmadianpour, M. Omair Ahmad · 2004
This paper presents a fast block-based motion estimation algorithm based on a bit plane technique. This algorithm can produce the eligible candidates for finding the enhanced motion vectors. The proposed method translates the expensive 2D block-matching problem to a simpler 1D matching by choosing some blocks as eligible candidates and eliminating the others. The bit-plane idea combined with the enhanced motion vector leads to a novel motion estimation algorithm. This novel algorithm offers computational scalability through two parameters, so the speed/performance trade-off of the proposed method can easily be controlled. Experiments show that the proposed method is several times faster than the full search algorithm and it produces a better prediction performance. There are some cases in which existing motion estimation techniques obtain a false motion vector with a huge prediction error, while the proposed method can find an enhanced motion vector with an excellent accuracy.
Cited by 3
Jinha Choi · Optical Engineering · 2009
We propose a motion vector memory reduction scheme for the H.264 spatial scalable motion estimation. The spatial scalable prediction of H.264 scalable video coding requires a significant amount of motion vector bits from the previous layer motion prediction. This motion vector causes the Internal memory size to increase, which may result in increasing hardware cost and power consumption. To reduce the memory size of the motion vector, we propose a motion vector bit-compression scheme of the interlayer motion estimation. The proposed compression scheme uses the difference value of current motion vector and previous motion vector to get a probability for entropy coding. In addition, the proposed scheme modifies a variable length coding table of the H.264 system as a simple entropy coding table. The proposed scheme reduces the motion vector-storing bit by ~66.5% with less changes in hardware size.
Cited by 1Open access