SVEF: an open-source experimental evaluation framework for H.264 scalable video streaming

Detti, Andrea; Bianchi, Giuseppe; Pisa, Claudio; Proto, Francesco Saverio; Loreti, Paola; Kellerer, Wolfgang; Thakolsri, Srisakul; Widmer, Joerg

doi:10.1109/iscc.2009.5202390

Cited by 48 publications

(36 citation statements)

References 14 publications

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“…Concerning simulation platforms for scalable video, in recent years, have been implemented few solutions, such as SVEF (Scalable Video-streaming Evaluation Framework) [16]. SVEF is a tools-set for empirical evaluation of real-time SVC streaming.…”

Section: Related Workmentioning

confidence: 99%

“…Figure 3 illustrates the workflow of the SVCEval-RA evaluation framework. The software modules inherited from the JSVM (Joint Scalable Video Model) package [38] and SVEF (Scalable Video coding Streaming Evaluation Framework) scripts [16] are represented in grey. The whole process, from the encoding of the original video source to the evaluation after the streaming over a simulated network can be summarized in four phases, better detailed in the following subsections: encoding, pre-processing, simulation and post-processing.…”

Section: The Svceval-ra Evaluation Frameworkmentioning

confidence: 99%

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SVCEval-RA: an evaluation framework for adaptive scalable video streaming

Castellanos

Guerri

Arce

2015

Multimed Tools Appl

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Abstract. Multimedia content adaption strategies are becoming increasingly important for effective video streaming over the actual heterogeneous networks. Thus, evaluation frameworks for adaptive video play an important role in the designing and deploying process of adaptive multimedia streaming systems. This paper describes a novel simulation framework for rate-adaptive video transmission using the Scalable Video Coding standard (H.264/SVC). Our approach uses feedback information about the available bandwidth to allow the video source to select the most suitable combination of SVC layers for the transmission of a video sequence. The proposed solution has been integrated into the network simulator NS-2 in order to support realistic network simulations. To demonstrate the usefulness of the proposed solution we perform a simulation study where a video sequence was transmitted over a three network scenarios. The experimental results show that the Adaptive SVC scheme implemented in our framework provides an efficient alternative that helps to avoid an increase in the network congestion in resource-constrained networks.Improvements in video quality, in terms of PSNR (Peak Signal to Noise Ratio) and SSIM (Structural Similarity Index) are also obtained.

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Section: Related Workmentioning

confidence: 99%

Section: The Svceval-ra Evaluation Frameworkmentioning

confidence: 99%

SVCEval-RA: an evaluation framework for adaptive scalable video streaming

Castellanos

Guerri

Arce

2015

Multimed Tools Appl

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“…Four varied content (factory, tractor, marathon and touchdown) 10 second long sequences were generated with 5 temporal levels and 4 quality levels, using Coarse Grain Scale (CGS) scheme, Table 1. Using source content and a Bernoulli loss model implemented in the SVEF framework [15], different scenarios were combined with source sequences to provide a total of 48 pairs of sequences. The reference sequence corresponds to the output of a non-adaptive system.…”

Section: Materials and Environmentmentioning

confidence: 99%

Adaptive Streaming: A subjective catalog to assess the performance of objective QoE metrics

Álvarez

Pozueco

Cabrero

et al. 2014

NPA

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Scalable streaming has emerged as a feasible solution to resolve users' heterogeneity problems. Scalable Video Streaming (SVC) is the technology that has served as the definitive impulse for the growth of streaming adaptive systems. Systems need to incorporate user's Quality of Experience (QoE) in the layer switching algorithms. This paper characterizes the relation between human decisions and objective metrics that could be mapped into systems. We have performed extensive subjective experiments to corroborate the preference towards adaptive systems when compared to traditional non-adaptive systems. The resulting subjective scores are correlated with most relevant Full Reference (FR) objective metrics. We obtain an exponential relationship between human decisions and the same decisions expressed as a difference of objective metrics. A strong correlation with subjective scores validates objective metrics to be used as aid in the adaptive decision taking algorithms to improve overall systems performance. Results show that, among the evaluated objective metrics, PSNR is the metric that provide worse results in terms of reproducing the human decisions.

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“…The Scalable Video coding streaming Evaluation Framework (SVEF) [5] is frame work for evaluating the performance of H.264/SVC format. It is the chain of software including JSVM [6] (joint scalable video model) packages.…”

Section: Svef Evaluation Frameworkmentioning

confidence: 99%

Packet End To End Delay Evaluation of AODV, AOMDV, DSR and DSDV in H.264 Streaming Video Transmission over MANETs

Sharma¹,

Negi²,

Sharma³

2014

IJIRSET

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ABSTRACT:With the significant increase in the demand of streaming videos over wireless networks leads to the huge challenge of providing high quality of services and standards to the users. So it is important to analyse the performance of streaming video transmission over mobile ad-hoc networks. In this paper, we scrutinize and evaluate the four routing protocols to check the performance of network parameters over varying fragment sizes. The fragment size plays the critical role in the traffic management of the network. The work is carried out using NS-2 and the routing protocols used are (AODV, AODMV, DSDV and DSR) for the different QoS metrics (average end to end packet delay and packet loss rate). Investigation leads to the results which help in tuning the network parameters for enhanced performance.

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SVEF: an open-source experimental evaluation framework for H.264 scalable video streaming

Cited by 48 publications

References 14 publications

SVCEval-RA: an evaluation framework for adaptive scalable video streaming

SVCEval-RA: an evaluation framework for adaptive scalable video streaming

Adaptive Streaming: A subjective catalog to assess the performance of objective QoE metrics

Packet End To End Delay Evaluation of AODV, AOMDV, DSR and DSDV in H.264 Streaming Video Transmission over MANETs

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