Temporal Motion Prediction for Fast Motion Estimation in Multiple Reference Frames

Rao, G. Nageswara; Gupta, Pooja

doi:10.1109/isspit.2006.270911

Cited by 3 publications

(4 citation statements)

References 5 publications

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“…Various fast algorithms 4,6,[16][17][18][19][20][21][22][23][24][25][26][27] have been proposed in the literature to reduce the computational complexity caused by MRF-ME. These algorithms can be classified into two categories.…”

Section: Introductionmentioning

confidence: 99%

“…6,14,15,[17][18][19][20][21] The condition always depends on spatial and temporal correlation in video sequences. 16,27 However, the early termination approach might select an undesirable reference frame, and the threshold value for early termination usually relies on the characteristics of video sequences. In other words, more reference frames are needed for sequences with fast motion activities, resulting in increased computational complexity.…”

Section: Introductionmentioning

confidence: 99%

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Reliable tracking algorithm for multiple reference frame motion estimation

Lee

Chan

et al. 2011

J. Electron. Imaging

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Abstract. Multiple reference frame motion estimation (MRF-ME) is one of the most crucial tools in H.264/AVC to improve coding efficiency. However, it disciplines an encoder by giving extra computational complexity. The required computation proportionally expands when the number of reference frames used for motion estimation increases. Aiming to reduce the computational complexity of the encoder, various motion vector (MV) composition algorithms for MRF-ME have been proposed. However, these algorithms only perform well in a limited range of reference frames. The performance deteriorates when motion vector composition is processed from the current frame to a distant reference frame. In this paper, a reliable tracking mechanism for MV composition is proposed by utilizing only the relevant areas in the target macroblock and taking different paths through a novel selection process from a set of candidate motion vectors. The proposed algorithm is especially suited for temporally remote reference frames in MRF-ME. Experimental results show that compared with the existing MV composition algorithms, the proposed one can deliver a remarkable improvement on the rate-distortion performance with similar computational complexity.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Reliable tracking algorithm for multiple reference frame motion estimation

Lee

Chan

et al. 2011

J. Electron. Imaging

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“…Many methods have been proposed to reduce the computation [1][2][3][4][5][6][7][8][9][10][11] and the memory access [12,13] for the MRF-ME. In [1][2][3][4], the motion vectors between two successive reference frames are used to predict the optimal motion vectors between the current frame and the reference frames (second to the oldest).…”

Section: Introductionmentioning

confidence: 99%

“…In [1][2][3][4], the motion vectors between two successive reference frames are used to predict the optimal motion vectors between the current frame and the reference frames (second to the oldest). These approaches effectively simplify the complexity of the MRF-ME but are more suitable for software-oriented implementations.…”

Section: Introductionmentioning

confidence: 99%

Avoiding unnecessary frame memory access and multi-frame motion estimation computation in H.264/AVC

Lin

Chen

2008

2008 IEEE International Symposium on Circuits and Systems (ISCAS)

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H.264/AVC video compression standard uses multiple reference frame motion estimation (MRF-ME) to enhance the coding performance. The required frame memory accesses and the computational cost of the MRF-ME, however, are very high. This paper proposes an approach which exploits the characteristic of a constant luminance macroblock (L-MB) to avoid unnecessary frame memory accesses and MRF-ME computation. Simulation results show that the proposed scheme can reduce about 43% of the frame memory accesses and 33% of the MRF-ME computation for low motion video sequences without any PSNR degradation and bit-rate increase.

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