Ultra high definition HEVC DASH data set

Feuvre, Jean Le; Thiesse, J-M.; Parmentier, Matthieu; Raulet, Mickaël; Daguet, C

doi:10.1145/2557642.2563672

Cited by 45 publications

(23 citation statements)

References 5 publications

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“…His current research interest include super resolution upscaling, image deblurring and denoising, and its application to media production and interactive TV. [44], based on 238 frames extracted from the HEVC DASH dataset [42]. The frames 125 and 224 of our subsequence are shown.…”

Section: Discussionmentioning

confidence: 99%

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Non-Parametric Blur Map Regression for Depth of Field Extension

D'Andres

Salvador

Kochale

et al. 2016

IEEE Trans. on Image Process.

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Abstract-Real camera systems have a limited depth of field (DOF) which may cause an image to be degraded due to visible misfocus or too shallow DOF. In this paper, we present a blind deblurring pipeline able to restore such images by slightly extending their DOF and recovering sharpness in regions slightly out-of-focus. To address this severely ill-posed problem, our algorithm relies first on the estimation of the spatiallyvarying defocus blur. Drawing on local frequency image features, a machine learning approach based on the recently introduced Regression Tree Fields is used to train a model able to regress a coherent defocus blur map of the image, labeling each pixel by the scale of a defocus point-spread-function. A non-blind spatiallyvarying deblurring algorithm is then used to properly extend the DOF of the image. The good performance of our algorithm is assessed both quantitatively, using realistic ground truth data obtained with a novel approach based on a plenoptic camera, and qualitatively with real images.Index Terms-Out-of-focus deblurring, extension of depth of field, Regression tree fields, defocus blur map.

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Section: Discussionmentioning

confidence: 99%

“…We finally perform a real experiment in the context of video deblurring. It is based on the HEVC DASH dataset [42], which is a real-life professional edit of several sequences shot for the 4Ever project [43]. Two (cropped) frames of the subsequence we have used are shown in Fig.…”

Section: B Application To Real Datamentioning

confidence: 99%

Non-Parametric Blur Map Regression for Depth of Field Extension

D'Andres

Salvador

Kochale

et al. 2016

IEEE Trans. on Image Process.

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“…To make the client access the video files via HTTP, Apache HTTP server was installed and configured on the server. The dataset used for analysing streaming with MPTCP was the public UHD HEVC-DASH dataset in [15]. Video codec used was H.265 and media encapsulation format was MP4.…”

Section: Methodsmentioning

confidence: 99%

“…UHD offers high pixel resolution, high frame rate (HFR) of about 50 to 120 frames per second, and colour fidelity for high dynamic range imaging. [15] …”

Section: Uhd Hevcmentioning

confidence: 99%

Experimental performance analysis of multipath TCP path characteristics in streaming UHD HEVC-dash over wireless networks

Wejin¹,

Amca²

2018

IJET

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The multiple interfaces in modern devices today have given great promise in enhancing multimedia service delivery over wireless networks. However, the IP coupled nature of the TCP/IP protocol inhibits the simultaneous use of these interfaces. Multipath TCP (MPTCP), a protocol undergoing IETF standardization has been developed to simultaneously use multiple interfaces for service delivery over the Internet. In this paper, we studied the effect of MPTCP paths characteristics in streaming Ultra High Definition, High Efficiency Video Codec (UHD HEVC-DASH) while connected to multiple wireless access points. The findings though specific instead of general, reveal that under balanced and unbalanced network paths, MPTCP offers good Quality of Experience (QoE) compared to SPTCP. However, with variability in latency, and packet loss between paths, MPTCP underperforms compared to SPTCP in terms of video buffering in the unbalanced network case, and high packet retransmission rate in either balanced or unbalanced network paths.

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“…Another vital parameter for HAS is segment length that indicates the minimum video period, elapsing which quality adjustment can occur in terms of bitrate and other settings [64,65,66]. As an example, for a live streaming, the video content is available at the location of server and simultaneously user is viewing at client side, which will ensure a low overall delay by the system.…”

Section: Segment Lengthmentioning

confidence: 99%

Survey of Transportation of Adaptive Multimedia Streaming service in Internet

Taha

Lloret

Cánovas

et al. 2017

NPA

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Streaming media systems such as YouTube, Netflix, and Apple Music are reining the multimedia world with frequent popularity among users. A key concern of quality perceived for video streaming applications over Internet is the Quality of Experience (QoE) that users experience. Due to changing network conditions, bit rate and initial delay, the multimedia file freezes or provides poor video quality to the end users. Researchers across industry and academia have explored HTTP Adaptive Streaming (HAS), which splits the video content into multiple segments and offers the clients varying qualities. The video player at the client side plays a vital role in buffer management and choosing the appropriate bit rate for each segment of video to be transmitted. A higher bit rate transmitted video pauses in between whereas, a lower bit rate video lacks in quality, requiring a tradeoff between them. The need of the hour was to adaptively vary bit rate and video quality to match the transmission media conditions. Furthermore, the main aim of this paper is to give an overview on the state of the art of HAS techniques across multimedia and networking domains. A detailed survey was conducted to analyze challenges and solutions in adaptive streaming algorithms, QoE, network protocols, buffering, etc. It also focuses on various challenges on QoE influence ISSN 1943-3581 2017 www.macrothink.org/npa 86 factors in a fluctuating network condition, which are often ignored in present HAS methodologies. Moreover, this survey will enable network and multimedia researchers a fair amount of understanding about the latest happenings of adaptive streaming and the necessary improvements that can be incorporated in future developments. Network Protocols and Algorithms

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Ultra high definition HEVC DASH data set

Cited by 45 publications

References 5 publications

Non-Parametric Blur Map Regression for Depth of Field Extension

Non-Parametric Blur Map Regression for Depth of Field Extension

Experimental performance analysis of multipath TCP path characteristics in streaming UHD HEVC-dash over wireless networks

Survey of Transportation of Adaptive Multimedia Streaming service in Internet

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