2003
DOI: 10.1007/978-3-540-44871-6_126
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Low Complexity Motion Estimation Based on Spatio-temporal Correlations

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Cited by 1 publication
(2 citation statements)
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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%
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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%
“…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.…”
mentioning
confidence: 99%