2014 IEEE 16th International Workshop on Multimedia Signal Processing (MMSP) 2014
DOI: 10.1109/mmsp.2014.6958822
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Iterative hierarchical true motion estimation for temporal frame interpolation

Abstract: Temporal frame interpolation is an important problem in many areas of modern video processing. However the task of accurate motion estimation for temporal interpolation is an open issue. In this paper we propose a new motion estimation algorithm for motion compensated frame interpolation. The developed algorithm is consistent with the conventional model of true motion and can be considered as a method of local minimization for the optimization problem defined within this model. The evaluation of the algorithm … Show more

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Cited by 17 publications
(16 citation statements)
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References 18 publications
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“…Veselov and Gilmutdinov [7] is about 10 times faster than the proposed method, while our BOA-TFI is around three times faster than Jeong et al [6].…”
Section: B) Processing Timesmentioning
confidence: 63%
See 3 more Smart Citations
“…Veselov and Gilmutdinov [7] is about 10 times faster than the proposed method, while our BOA-TFI is around three times faster than Jeong et al [6].…”
Section: B) Processing Timesmentioning
confidence: 63%
“…The first row shows the full frame. The second to last row show crops of the ground truth, proposed BOA-TFI, Jeong et al [6] and Veselov and Gilmutdinov [7], respectively.…”
Section: A) Results On Natural Sequencesmentioning
confidence: 99%
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“…Since both the technical progress of frame-interpolation schemes [11][12][13][14][15][16] and the frame-interpolation module are expected to be commonly employed in next-generation VR headsets [17], users could have stable high-refresh-rate vision with a lower downlink (DL) VR video frame rate. Sensing data, which is not fed back to computing machines, including VR-ready PCs, can be utilized by the frame-interpolation module to generate interpolation frames, with accurate moving data from the user.…”
Section: Introductionmentioning
confidence: 99%