Spatio-temporal correlation based fast motion estimation algorithm for MPEG-2

Ramkishor, K.; Krishna, S.

doi:10.1109/acssc.2001.986909

Cited by 16 publications

(4 citation statements)

References 5 publications

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“…Although these may not be always valid, especially when the moving scenes contain complex motions, they are still reasonable for most cases in the real world. Based on this hypothesis, many algorithms have been proposed to efficiently exploit the spatial or temporal correlations to reduce computations of the motion estimation [21,[51][52][53][54][55][56][57][58][59][60][61][62][63][64][65][66][67][68][69], mainly in three ways: 1) Find a good starting point (predictor) that may be close to the global minimum,…”

Section: Fast Bmas Using Temporal/spatial Correlationsmentioning

confidence: 99%

“…In [54,62] [67] where it was also observed that motion vectors are more median-biased than center-biased. Before determining the starting point, any neighboring motion vectors can be used as the best match based on a certain criterion such as thresholding technique [51,59,60,64] and correlations among the neighboring motion vectors [65] or both [67].…”

Section: Fast Bmas Using Temporal/spatial Correlationsmentioning

confidence: 99%

“…Neighboring blocks used in some algorithms[52,[59][60][61][62][63][64][65][66][67] (spatial and temporal blocks together) tion from the neighboring blocks to adaptively change the size of the MSW, while a neighboring motion vector can be directly used as the best match based on thresholding technique in another algorithm.…”

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confidence: 99%

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Fast motion estimation for video coding

Qi¹

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First and foremost, I would like to express my earnest appreciation from the bottom of my heart to my supervisor, Dr. Zhu Ce, for his professional guidance, invaluable support and kindly encouragement during my master study as well as his constructive comments on this thesis. It is my pleasure to spend around two years with many talent and kind friends in the Media Lab. I cherish the friendship and thank them for their selfless help. This thesis is dedicated to my parents. Their love and inspiration are always with me.

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Section: Fast Bmas Using Temporal/spatial Correlationsmentioning

confidence: 99%

Section: Fast Bmas Using Temporal/spatial Correlationsmentioning

confidence: 99%

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Fast motion estimation for video coding

Qi¹

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“…Among the various methods proposed for adjusting search ranges [6]- [11], those in [6] and [7], a list of search range candidates is previously prepared, and a single range is chosen from it on the basis of either prediction error values or of the motion vector values previously obtained for adjacent blocks. Both of these methods suffer, however, from the fact that the number of search-range candidates is insufficient to reflect meaningfully the large number of variations in actual video motion.…”

Section: Introductionmentioning

confidence: 99%

Fast and Accurate Motion Estimation Algorithm By Adaptive Search Range and Shape Selection

Yamada

Ikekawa

Kuroda

Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005.

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This paper presents a fast and accurate motion estimation algorithm. To obtain accurate motion vectors while minimizing computational complexity, we adjust the search range for each frame and each block to suit the motion level of the video. An appropriate search range for each frame is determined on the basis of motion vectors and prediction errors obtained for the previous frame. At each block, the search range is determined on the basis of the search range of its frame and of the motion vector values of all adjacent blocks for which those values have already been obtained. With our algorithm, since narrow search ranges are chosen for areas in which little motion occurs, computational complexity can be reduced without degrading estimation accuracy. Since wide search ranges are chosen for areas of significant motion, good video-quality encoding can be maintained. In the encoding of an SDTV size video, the addition of range adjustment results in a reduction in the computational complexity of motion estimation of roughly 65%, while maintaining the same video quality.

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H.264 search window size algorithm for fast and efficient video coding with single pixel precision and no background estimation for motion detection

Bailo¹,

Bariani²,

Chiappori³

et al.

CCNC 2006. 2006 3rd IEEE Consumer Communications and Networking Conference, 2006.

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H.264 is the video standard needed for new high band requests of multimedia services such as video on demand, videoconference or videosurveillance. These applications require high video quality with the lowest possible band occupation. The new video coding standard H.264 seems to be answer to fulfill these requirements.Anyway, while fulfilling the requested quality-bandwidth ratio, the H.264 encoder complexity is largely increased if compared with previous standards, mainly because of the high computational cost of the Motion Estimation (ME) module that is the core of this standard video encoder.In this paper, we propose an enhancement to our innovative algorithm for a further complexity reduction of the ME module. The main idea is to make dynamically modifiable a previously static H.264 coder parameter: the size of the search window in ME. A Faster Motion Detection (MD) module, pixel precise and without background estimation, has been added to the video coder in order to compute the search window size. Moreover this method is valid for every kind of video stream and not only for sequences having a static background, thanks to the pixel precision of the motion detection.In the proposed solution, the reduction of the number of calculated SAD (Sum-of-Absolute-Differences) allows to decrease the encoder complexity both in low and high complex sequences. This paper illustrates the behavior of the Search Window Estimation (SWE) algorithm in both the old and the new algorithm version. The obtained results are then compared with jm86 full search and fast ME using different quantization values.

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Spatio-temporal correlation based fast motion estimation algorithm for MPEG-2

Cited by 16 publications

References 5 publications

Fast motion estimation for video coding

Fast motion estimation for video coding

Fast and Accurate Motion Estimation Algorithm By Adaptive Search Range and Shape Selection

H.264 search window size algorithm for fast and efficient video coding with single pixel precision and no background estimation for motion detection

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