No-Reference metrics for video streaming applications

Multimedia Tools and Applications, 2008

This paper 1 deals with monitoring user perception of multimedia presentations in a Universal Multimedia Access (UMA) enabled system using objective no-reference (NR) metrics. These NR metrics are designed for an UMA-enabled system, in a novel architecture, for a multimedia viewer. The first metric measures block-edge impairments in a video frame at the receiver end, based on the observation that they occur in regions with low spatial activity. The second metric evaluates the quality of the reconstructed video frame in the event of packet loss. Here, the structure of the artifact is itself exploited for the evaluation. Both the metrics involve low computational complexity and are feasible for real-time monitoring of streaming video in a multimedia communication scenario. Further, in rate-adaptive streaming of video, these metrics could serve as feedback parameters to dynamically adapt the video rates based on network congestion.

Journal of Visual Communication and Image Representation, 2015

Video quality is a key factor in modern video streaming systems. Video compression artifacts affect it but also delay, jitter and packet loss may compromise it. Objective metrics have been proposed to emulate the human visual system: several experimental works have evaluated their adherence to opinions expressed by real users. Instead of dealing with subjective tests, we focused on the effects of network packet losses on objective metrics: since quality metrics are generally computationally intensive, a convenient approach could consist in inferring information about transmission quality from network impairment statistics. We did experimental tests on two computer-animated videos, whose high color contrasts allow a fair comparison between content dependent and content independent metrics. We studied the encoding parameters that minimize/maximize the values of some metrics (PSNR, BI-PSNR, SSIM, 3SSIM, MSSSIM, VQM) for several packet loss percentages. We analyzed also the Empirical Cumulative Density Function of the degradations of quality metrics.

IEEE Internet Computing, 2000

E d it o r : S io b h á n C l a r ke • s iob ha n .c lar ke @c s .t cd . ie F or consumer video services, real-time streaming applications such as IPTV have stringent service-level agreement (SLA) requirements. We can describe key service-level requirements -commonly specified in SLAsfor IP-based video transport services in terms of delay, jitter, and loss. As we described in the first part of this series, 1 Differentiated Services (Diffserv) IP quality-of-service (QoS) mechanisms can help ensure that service providers meet SLA requirements for delay and jitter for video-streaming services. Such mechanisms can't control packet loss due to lower-layer errors or network connectivity issues, and these network events can result in visual impairments to the video service.

The Scientific World Journal, 2014

When comparing the performance of video coding approaches, evaluating different commercial video encoders, or measuring the perceived video quality in a wireless environment, Rate/distortion analysis is commonly used, where distortion is usually measured in terms of PSNR values. However, PSNR does not always capture the distortion perceived by a human being. As a consequence, significant efforts have focused on defining an objective video quality metric that is able to assess quality in the same way as a human does. We perform a study of some available objective quality assessment metrics in order to evaluate their behavior in two different scenarios. First, we deal with video sequences compressed by different encoders at different bitrates in order to properly measure the video quality degradation associated with the encoding system. In addition, we evaluate the behavior of the quality metrics when measuring video distortions produced by packet losses in mobile ad hoc network scenarios with variable degrees of network congestion and node mobility. Our purpose is to determine if the analyzed metrics can replace the PSNR while comparing, designing, and evaluating video codec proposals, and, in particular, under video delivery scenarios characterized by bursty and frequent packet losses, such as wireless multihop environments.

Journal of Multimedia, 2006

Video traces contain information about encoded video frames, such as frame sizes and qualities, and provide a convenient method to conduct multimedia networking research. Although widely used in networking research, these traces do not allow to determine the video quality in an accurate manner after networking transport that includes losses and delays.

Elektronika ir Elektrotechnika, 2016

In this paper a simple and robust method for estimation of distorted video quality, which is perceived by human observer in mobile video streaming applications, is proposed and assessed. Increasing bandwidth of mobile communication systems expand the variety of offered multimedia services such as video streaming. However, the quality of these services is very dependent on rapidly varying mobile communication conditions. Most widely used video quality estimation methods, such as Peak Signal to Noise Ratio (PSNR), Structural Similarity (SSIM), and Video Quality Metric (VQM) are based on the presence of full or reduced reference video. These methods could be used to assess video quality of video transmission system only during test stage and in the limited number of scenarios. In order to assess user experienced video quality in real conditions, methods with no reference must be employed. Such existing methods as video quality metric use bit-error rate that has low correlation with human perceived video quality. More precise methods usually are too complex and require too much processing power that cannot be tolerated in handheld mobile devices. In this paper it is shown that developed no reference low complexity video quality estimation method based on H.264/AVC video stream packet structure delivers estimate of received video quality comparable with results of subjective MOS tests. Index Terms-H.264 coding; mobile video streaming; video quality assessment; VQM.

IEEE Transactions on Circuits and Systems for Video Technology, 2000

Video transmitted over an error-prone network may be received at the decoder with degradations due to packet losses. No-reference quality monitoring algorithms are the most practical way to measure the quality of the received video, since they do not impose any change with respect to the network architecture. Conventionally, these methods assume the availability of the corrupted bitstream. In some situations this is not possible, e.g., because the bitstream is encrypted or processed by third-party decoders, and only the decoded pixel values can be used. The major issue in this scenario is the lack of knowledge about which regions of the video have been actually lost, which is a fundamental ingredient for estimating channel-induced distortion. In this paper, we propose a maximum a posteriori estimation of the pattern of lost macroblocks, which assumes the knowledge of the decoded pixels only. This information can be used as input to a no-reference quality monitoring system, which produces an accurate estimate of the mean-square-error (MSE) distortion introduced by channel errors. The results of the proposed method are well correlated with the MSE distortion computed in fullreference mode, with a linear correlation coefficient equal to 0.9 at frame level and 0.98 at sequence level.

A measurement study is conducted of video streaming across a testbed with routers typical of those found at bottlenecks on the wired Internet. During 'bursty' traffic packet loss is not always fairly distributed between background flows and a video stream. The paper shows that packet loss indications may be unreliable whereas packetby-packet delay, an alternative metric, has the ability to closely track queue length, responding to available bandwidth in a timely manner.

IEEE Communications Surveys & Tutorials, 2000

ith the increasing popularity of networked multimedia applications, video data is expected to account for a large portion of the traffic in the Internet of the future and next-generation wireless systems. For transport over networks, video is typically encoded (i.e., compressed) to reduce the bandwidth requirements. Even compressed video, however, requires large bandwidths of the order of hundreds of kb/s or Mb/s, as will be shown later in this tutorial. In addition, compressed video streams typically exhibit highly variable bit rates (VBR) as well as long range dependence (LRD) properties, as will be demonstrated later in this tutorial. This, in conjunction with the stringent Quality of Service (QoS) requirements (loss and delay) of video traffic, makes the transport of video traffic over communication networks a challenging problem. As a consequence, in the last decade the networking research community has witnessed an explosion in research on all aspects of video transport. The characteristics of video traffic, video traffic modeling, as well as protocols and mechanisms for the efficient transport of video streams, have received a great deal of interest among networking researchers and network operators.

IEICE Proceeding Series

As network researchers prefer evaluate the effectiveness of the network before deploying the protocols in real networks, video traces, which give the sizes of the individual video frames in a video sequence, have been emerging as convenient video characterizations for networking studies. This paper proposes a system named VSS (Video Streaming Simulation) for comprehensive video delivered quality evaluation using traffice traces in RTP/UDP/IP network simulation environment.