Multiview Plus Depth Video Coding With Temporal Prediction View Synthesis

Purica, Andrei; Mora, Elie Gabriel; Pesquet‐Popescu, Béatrice; Cagnazzo, Marco; Ionescu, Bogdan

doi:10.1109/tcsvt.2015.2389511

Cited by 43 publications

(13 citation statements)

References 33 publications

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“…The 3D Multi‐View Video Coding (MVC) is an extension of H.264/AVC video coding. Recently, it has received a broad attentiveness, and it will rapidly take place of 2‐dimensional video in different and important applications . In the 3D‐MVC, the 3D Video (3DV) consists of various video streams captured for the same object with different cameras.…”

Section: Introductionmentioning

confidence: 99%

“…Recently, it has received a broad attentiveness, and it will rapidly take place of 2dimensional video in different and important applications. [1][2][3][4][5] In the 3D-MVC, the 3D Video (3DV) consists of various video streams captured for the same object with different cameras. Thence, it is required to perform sufficient compression to fulfill bandwidth requirements, whilst preserving a decisive Three-Dimensional Multi-View Video (3D MVV) reception quality.…”

Section: Introductionmentioning

confidence: 99%

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Performance evaluation of enhanced error correction algorithms for efficient wireless 3D video communication systems

El‐Shafai

El‐Rabaie

El-Halawany

et al. 2017

Int J Communication

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Summary In the Three‐Dimensional Multi‐View Video (3D MVV) coding prediction structure, the coded bit‐streams may be dropped down due to error transmissions. So, it is compulsory to recover the corrupted Macro‐Blocks (MBs) at the decoder utilizing efficient Error Concealment (EC) post‐processing techniques. The EC methods exploit the temporal, inter‐view, and spatial matching among 3D MVV views and frames without any alterations in the encoder software or hardware or in the transmission rate. They retrieve the Disparity Vectors (DVs) and Motion Vectors (MVs) of the erroneous MBs. To enhance the received 3D MVV quality, we suggest several optimized schemes to reconstruct the lost and erroneous MBs of inter‐encoded and intra‐encoded frames. A hybrid method combining the Circular Scan Order Interpolation Algorithm (CSOIA) and Partitioning Motion Compensation Algorithm (PMCA) is proposed for intra‐frame EC. For inter‐corrupted MBs, a hybrid method comprising Directional Textural Motion Coherence Algorithm (DTMCA) and Directional Interpolation Error Concealment Algorithm (DIECA) is suggested. Experimental outcomes on several 3D MVV frames demonstrate that the suggested EC algorithms have more robustness to both heavily random and slice losses. They objectively and subjectively work better than the state‐of‐the‐art EC techniques. The proposed work achieves high 3D MVV quality with an improved average Peak Signal‐to‐Noise Ratio (PSNR) gain up to 2.45 to 4.55 dB compared with traditional EC algorithms at Packet Loss Rates (PLRs) of 40%.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Performance evaluation of enhanced error correction algorithms for efficient wireless 3D video communication systems

El‐Shafai

El‐Rabaie

El-Halawany

et al. 2017

Int J Communication

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“…The information variety between these representations can be used to obtain a higher quality video. Similar scenarios can be encountered when enhancing older videos that are only available in compressed form or when working with MultiView plus Depth (MVD) [2] video transmission systems where the problem of image alignment is achieved through depth computed disparity.…”

Section: Introduction and State Of The Artmentioning

confidence: 92%

A Convex Optimization Framework for Video Quality and Resolution Enhancement From Multiple Descriptions

Purica

Boyadjis

Pesquet‐Popescu

et al. 2019

IEEE Trans. on Image Process.

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“…Efficient compression of MVD data is a very important task in 3DTV processing chain to achieve a wide spread acceptability of 3DTV and FTV technologies. Recently, it has received significant research efforts resulting in new compression friendly MVD representations [12][13][14][15][16][17] and efficient 3D video encoders. Multi-view Video Coding (MVC) [18] was standardized as an extension of Advanced Video Coding (AVC) [19] for multiview video (MVV) format to support the stereoscopic and autostereoscopic 3D displays [20].…”

Section: Introductionmentioning

confidence: 99%

No-reference quality metric for HEVC compression distortion estimation in depth maps

Farid

Lucenteforte

Grangetto

2019

SIViP

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Multiview video plus depth (MVD) is the most popular 3D video format due to its efficient compression and provision for novel view generation enabling the freeviewpoint applications. In addition to color images, MVD format provides depth maps which are exploited to generate intermediate virtual views using the depth image based rendering (DIBR) techniques. Compression affects the quality of the depth maps which in turn may introduce various structural and textural distortions in the DIBR synthesized images. Estimation of the compression related distortion in depth maps is very important for a high quality 3D experience. The task becomes challenging when the corresponding reference depth maps are unavailable e.g., when evaluating the quality on the decoder side. In this paper, we present a no-reference quality assessment algorithm to estimate the distortion in the depth maps induced by compression. The proposed algorithm exploits the depth saliency and local statistical characteristics of the depth maps to predict the compression distortion. The proposed 'depth distortion evaluator' (DDE) is evaluated on depth videos from standard MVD database compressed with the state-of-the-art high efficiency video coding (HEVC) at various quality levels. The results demonstrate that DDE can be used to effectively estimate the compression distortion in depth videos.

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Multiview Plus Depth Video Coding With Temporal Prediction View Synthesis

Cited by 43 publications

References 33 publications

Performance evaluation of enhanced error correction algorithms for efficient wireless 3D video communication systems

Performance evaluation of enhanced error correction algorithms for efficient wireless 3D video communication systems

A Convex Optimization Framework for Video Quality and Resolution Enhancement From Multiple Descriptions

No-reference quality metric for HEVC compression distortion estimation in depth maps

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