2019 Data Compression Conference (DCC) 2019
DOI: 10.1109/dcc.2019.00106
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A CU Split Early Termination Algorithm Based KNN for 360-Degree Video

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Cited by 7 publications
(12 citation statements)
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“…The average results for each algorithm are presented in Table 1, where InterTech is the result of employing all interframes prediction algorithms simultaneously (i.e., Early Skip, Reduced SR, and Reduced FME), and IntraTech is the combination of Reduced Intra Sizes and a previous work published at [11]. Table I also presents the average results of related works: Liu [12] and Ray [13] present proposals to accelerate the interframes prediction of ERP 360 videos, whereas Wang [14] and Zhang [15] propose to accelerate the intraframe prediction of ERP 360 videos. Liu [12] uses a KNN classifier to discard some unlikely block sizes during interframes prediction; Ray [13] discards unlikely block sizes during interframes prediction and reduces FME precision based on block position; Wang [14] discards some prediction modes and block sizes during intraframe prediction based on block position; and Zhang [15] evaluates the texture of the blocks to evaluate a subset of prediction modes and block sizes.…”
Section: Resultsmentioning
confidence: 99%
See 2 more Smart Citations
“…The average results for each algorithm are presented in Table 1, where InterTech is the result of employing all interframes prediction algorithms simultaneously (i.e., Early Skip, Reduced SR, and Reduced FME), and IntraTech is the combination of Reduced Intra Sizes and a previous work published at [11]. Table I also presents the average results of related works: Liu [12] and Ray [13] present proposals to accelerate the interframes prediction of ERP 360 videos, whereas Wang [14] and Zhang [15] propose to accelerate the intraframe prediction of ERP 360 videos. Liu [12] uses a KNN classifier to discard some unlikely block sizes during interframes prediction; Ray [13] discards unlikely block sizes during interframes prediction and reduces FME precision based on block position; Wang [14] discards some prediction modes and block sizes during intraframe prediction based on block position; and Zhang [15] evaluates the texture of the blocks to evaluate a subset of prediction modes and block sizes.…”
Section: Resultsmentioning
confidence: 99%
“…Table I also presents the average results of related works: Liu [12] and Ray [13] present proposals to accelerate the interframes prediction of ERP 360 videos, whereas Wang [14] and Zhang [15] propose to accelerate the intraframe prediction of ERP 360 videos. Liu [12] uses a KNN classifier to discard some unlikely block sizes during interframes prediction; Ray [13] discards unlikely block sizes during interframes prediction and reduces FME precision based on block position; Wang [14] discards some prediction modes and block sizes during intraframe prediction based on block position; and Zhang [15] evaluates the texture of the blocks to evaluate a subset of prediction modes and block sizes. It must be noted that Ray [13] uses the encoder Joint Exploration Model (JEM) [16], an exploratory encoder built on top of HEVC to evaluate new encoding tools for future video coding standards.…”
Section: Resultsmentioning
confidence: 99%
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“…For instance, several research works have been investigated on fast approaches for 360-degree video coding [98][99][100][101][102][103][104] but without any depth information, i.e. 3DoF.…”
Section: Role Of Depth Coding In Future Immersive Mediamentioning
confidence: 99%
“…3DoF. The algorithms proposed in [98][99][100] have fast intra prediction, while the works in [101,102,103] suggested having fast CU approaches and a fast PU approach, respectively. Besides, the algorithm in [104] developed adaptive motion vector (MV) resolution to achieve a low-complexity encoder.…”
Section: Role Of Depth Coding In Future Immersive Mediamentioning
confidence: 99%