120 lines
8.0 KiB
BibTeX
120 lines
8.0 KiB
BibTeX
@comment{x-kbibtex-encoding=utf-8}
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@inproceedings{DynamicTMVP2011,
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author = {Bin Li and Jizheng Xu and Houqiang Li},
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booktitle = {IEEE Visual Communications and Image Processing},
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doi = {10.1109/VCIP.2011.6115967},
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keywords = {decoding; entropy codes; video coding; HEVC; entropy decoding; error propagation; high efficiency video coding; parsing process; parsing robustness; syntax elements; Decoding; Encoding; Entropy; Indexes; PSNR; Robustness; Vectors},
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month = sep,
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pages = {1-4},
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title = {Parsing robustness in High Efficiency Video Coding - analysis and improvement},
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year = {2011}
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}
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@inproceedings{ErrorResilienceModeHEVC2016,
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author = {G. Kulupana and D. S. Talagala and H. K. Arachchi and A. Fernando},
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booktitle = {IEEE International Conference on Consumer Electronics (ICCE)},
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doi = {10.1109/ICCE.2016.7430531},
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keywords = {motion estimation; video coding; HEVC video transmission; error concealment techniques; error resilience aware motion estimation; high efficiency video coding; mode selection; Conferences; Consumer electronics},
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month = {Jan},
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pages = {85-86},
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title = {Error resilience aware motion estimation and mode selection for {HEVC} video transmission},
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url = {/home/joaoc/Dropbox/InstitutoTelec/PhD/Bibliography/ErrorResilience/HEVC/2016 - Error resilience aware motion estimation and mode selection for HEVC video transmission.pdf},
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url2 = {/home/joaoc/Dropbox/InstitutoTelec/PhD/Deliverables/Journal/2018_IEEETB_ConcealmentAware/related_work/2016 - Error resilience aware motion estimation and mode selection for HEVC video transmission.pdf},
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year = {2016}
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}
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@inproceedings{ErrorResilienceModeHEVC2017,
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author = {H. M. Maung and S. Aramvith and Y. Miyanaga},
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booktitle = {IEEE International Conference on Consumer Electronics (ICCE)},
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doi = {10.1109/ICCE.2017.7889360},
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keywords = {video coding; HEVC video transmission; ROI based coding mode selection; RPS method; WVGA; error resilience framework; high efficiency video coding; rate control algorithm; reference picture selection method; region-of-interest based coding mode selection; Bit rate; Conferences; Encoding; High efficiency video coding; Integrated circuits; Streaming media},
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month = {Jan},
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pages = {374-375},
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title = {Error resilience aware rate control and mode selection for {HEVC} video transmission},
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year = {2017}
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}
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@inproceedings{DualFrameME2015,
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author = {D. Liu and L. Wang and C. Li and Y. Hao and F. Yin},
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booktitle = {IEEE International Symposium on Multimedia (ISM)},
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doi = {10.1109/ISM.2015.103},
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keywords = {filtering theory; image coding; motion compensation; DFMC coding structure; Macroblock; end-to-end distortion model; error protection; error resilient coding structure; error resilient filter; extended dual frame motion compensation; frame level rate cost decision; level rate distortion cost decision; Bit rate; Decoding; Distortion; Encoding; Motion compensation; Rate-distortion; Streaming media; Error resilient; dual frame; motion compensation; rate distortion model},
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month = dec,
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pages = {331-334},
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title = {Error Protection with Extended Dual Frame Motion Compensation},
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year = {2015}
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}
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@inproceedings{HEVCROIErrorResilience2015,
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author = {H. M. Maung and S. Aramvith and Y. Miyanaga},
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booktitle = {15th International Symposium on Communications and Information Technologies (ISCIT)},
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doi = {10.1109/ISCIT.2015.7458352},
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keywords = {computational complexity; multimedia communication; video coding; video communication; CU-level intra refresh; HEVC video transmission; MR information; ROI-based error resilient algorithm; RPS algorithm; coding unit depth level; computation complexity; current rate control algorithm; feedback channel; high-efficiency video coding; low-delay application; moving region; reference picture selection algorithm; region-of-interest-based error resilient method; Algorithm design and analysis; Decoding; Delays; Distortion; Encoding; Streaming media; HEVC; error-propagation; error-resilient coding; region-of-interest; video transmission},
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month = oct,
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pages = {241-244},
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title = {Region-of-interest based error resilient method for {HEVC} video transmission},
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url = {/home/joaoc/Dropbox/InstitutoTelec/PhD/Bibliography/ErrorResilience/HEVC/2015 - Region-of-interest based error resilient method for HEVC video transmission.pdf},
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year = {2015}
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}
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@comment{jabref-meta: databaseType:bibtex;}
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@inproceedings{SliceImportance_ICHNRSR2015,
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author = {R. Perera and A. Fernando and T. Mallikarachchi and H. K. Arachchi and M. Pourazad},
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booktitle = {10th International Conference on Heterogeneous Networking for Quality, Reliability, Security and Robustness},
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doi = {10.1109/QSHINE.2014.6928661},
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issn = {},
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month = aug,
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number = {},
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pages = {63-69},
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title = {QoE aware resource allocation for video communications over {LTE} based mobile networks},
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volume = {},
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year = {2014}
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}
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@inproceedings{RateDistortionNN_VCIP2017,
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author = {B. Xu and X. Pan and Y. Zhou and Y. Li and D. Yang and Z. Chen},
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booktitle = {2017 IEEE Visual Communications and Image Processing (VCIP)},
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doi = {10.1109/VCIP.2017.8305151},
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issn = {},
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keywords = {convolution; feedforward neural nets; learning (artificial intelligence); rate distortion theory; video coding; H.265/HEVC; fully convolutional neural network; pixels-to-pixels mappings; rate information; fully connected layers; traditional CNN methods; rate-distortion modeling; structural similarity maps; CNN-based framework; SSIM maps; Distortion; Video coding; Rate-distortion; Image coding; Rate distortion theory; Testing; Convolutional neural networks; Rate-distortion model; convolutional neural network (CNN); H.265/HEVC; structural similarity; deep learning},
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month = dec,
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number = {},
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pages = {1-4},
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title = {{CNN}-based rate-distortion modeling for {H.265/HEVC}},
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url = {/home/joaoc/Dropbox/InstitutoTelec/Bibliography/NeuralNetworks/Video/2017 - CNN-Based Rate-Distortion Modeling for H.265 HEVC.pdf},
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volume = {},
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year = {2017}
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}
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@inproceedings{HEVCRoiIntraRefresh_DSP2016,
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author = {H. Maung and S. Aramvith and Y. Miyanaga},
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booktitle = {IEEE International Conference on Digital Signal Processing (DSP)},
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doi = {10.1109/ICDSP.2016.7868563},
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issn = {2165-3577},
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month = oct,
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number = {},
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pages = {286-290},
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title = {Improved region-of-interest based rate control for error resilient {HEVC} framework},
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volume = {},
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year = {2016}
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}
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@Article{HEVCWireless_2016,
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author="Psannis, Kostas E.",
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title={{HEVC} in wireless environments},
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journal="Journal of Real-Time Image Processing",
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year="2016",
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month=aug,
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day="01",
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volume="12",
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number="2",
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pages="509--516",
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abstract="The increasing demand for real-time applications with high and ultra-high-definition video urged the ITU-T and the ISO/IEC to join their forces to develop the next-generation video coding standard. The new coding standard that has been produced is known as High-Efficiency Video Coding (HEVC). The proposed HEVC standard fulfilled its target to achieve more than 50 {\%} improvement in video compression over the existing H.264 Advanced Video Coding standard, keeping comparable image quality, at the expense of increased computational complexity. Advances in wireless communications and mobile networking have dramatically increased the popularity of video services for mobile users, with video delivery at their fingertips. Delivering high perceptual quality video over wireless environments is challenging due to the changing channel quality and the variations in the importance of one source packet to the next for the end user's quality of experience. The main objective of this paper is to provide an overview over the new characteristics which are likely to be used in HEVC in wireless environments and discusses several research challenges. Experimental results demonstrate that for low-delay wireless video communications, the HEVC codec is more effective compare to previous H.264 codec and shows better overall performance. Both subjective and objective visual quality comparative study has been also carried out to validate the proposed approach.",
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issn="1861-8219",
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doi="10.1007/s11554-015-0514-6",
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url="https://doi.org/10.1007/s11554-015-0514-6"
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}
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