Pradip Paudyal

A study on the effects of quality of service parameters on perceived video quality

In this paper a video database, ReTRiEVED, to be used in evaluating the performances of video quality metrics is presented. The database contains 184 distorted videos obtained from eight videos of different content. Packet loss rate, jitter, delay, and throughput have been considered as possible distortions resulting from video transmission. Video sequences, collected subjective scores, and results of the performed analysis are made publicly available for the research community, for designing, testing and comparing objective video quality metrics. The analysis of the results shows that packet loss rate, throughput/bandwidth, and jitter have significant effect on perceived quality, while an initial delay does not significantly affect the perceived quality.

Impact of video content and transmission impairments on quality of experience

The analysis of the impact of video content and transmission impairments on Quality of Experience (QoE) is a relevant topic for the robust design and adaptation of multimedia infrastructures, services, and applications. The goal of this paper is to study the impact of video content on QoE for different levels of impairments. In more details, this contribution aims at i) the study of the impact of delay, jitter, packet loss, and bandwidth on QoE, ii) the analysis of the impact of video content on QoE, and iii) the evaluation of the relationship between content related parameters (spatial-temporal perceptual information, motion, and data rate) and the QoE for different levels of impairments.

QoS to QoE mapping model for wired/wireless video communication

Multimedia service providers have to deliver video content through bandwidth limited and error-prone networks with agreed level of perceived video quality to customers for specific applications. To this aim service providers must devise a strategy to monitor the perceived quality and automatically adapt it when necessary. Measuring perceived quality is challenging for service providers. So there is the need for a mapping model to predict perceived video quality from system related quality of service parameters. In this article performance comparison of widely used quality of service to quality of experience mapping models has been presented and optimal solution has been recommended for key quality of service parameters: jitter, delay, packet loss rate and throughput limitation. For this purpose the freely available video quality database ReTRiEVED has been used.

Towards the Perceptual Quality Evaluation of Compressed Light Field Images

Evaluation of perceived quality of light field images, as well as testing new processing tools, or even assessing the effectiveness of objective quality metrics, relies on the availability of test dataset and corresponding quality ratings. This paper presents SMART light field image quality dataset. The dataset consists of source images (raw data without optical corrections), compressed images, and annotated subjective quality scores. Furthermore, analysis of perceptual effects of compression on SMART dataset is presented. Next, the impact of image content on the perceived quality is studied with the help of image quality attributes. Finally, the performances of 2-D image quality metrics when applied to light field images are analyzed.

SMART: a light field image quality dataset

In this contribution, the design of a Light Field image dataset is presented. It can be useful for design, testing, and benchmarking Light Field image processing algorithms. As first step, image content selection criteria have been defined based on selected image quality key-attributes, i.e. spatial information, colorfulness, texture key features, depth of field, etc. Next, image scenes have been selected and captured by using the Lytro Illum Light Field camera. Performed analysis shows that the proposed set of images is sufficient for addressing a wide range of attributes relevant for assessing Light Field image quality.

A study of the impact of light fields watermarking on the perceived quality of the refocused data

Securing multimedia data from undesired manipulation is a widely investigated topic in the state of the art. A large number of techniques has been developed for protecting images, videos, and also audio from malicious attacks. Nowadays new imaging systems pose new challenges from the data protection point of view. In particular, plenoptic cameras allow to record multiple views of a scene by using a single camera in a single shot, thus avoiding the problems related to calibration and camera synchronization. In this contribution, a novel embedding scheme tuned to light fields is presented. The watermark is inserted in the horizontal and vertical detail subbands of the first level of the Haar wavelet transform. The aim of this work is twofold: the design of a water-marking system that does not affect the depth map estimation procedure and therefore the refocusing procedure and the 3D scene reconstruction. On the other hand, the impact of light field data modification with respect to the perceived quality has been investigated. Experimental tests, both objective and subjective, have been carried out for assessing the performances of the proposed algorithm.

Evaluation of the Effects of Transmission Impairments on Perceived Video Quality by exploiting ReTRiEVED Dataset

Abstract. The robust design and adaptation of multimedia networks relies on the study of the influence of potential network impairments on the perceived quality. Video quality may be affected by network impairments, such as delay, jitter, packet loss, and bandwidth, and the perceptual impact of these impairments may vary according to the video content. The effects of packet loss and encoding artifacts on the perceived quality have been widely addressed in the literature. However, the relationship between video content and network impairments on the perceived video quality has not been deeply investigated. A detailed analysis of ReTRiEVED test video dataset, designed by considering a set of potential network impairments, is presented, and the effects of transmission impairments on perceived quality are analyzed. Furthermore, the impact on the perceived quality of the video content in the presence of transmission impairments is studied by using video content descriptors. Finally, the performances of well-known quality metrics are tested on the proposed dataset.

Study of the effects of video content on quality of experience

In this article the effects of video content on Quality of Experience (QoE) have been presented. Delivery of the video content with high level of QoE from bandwidth-limited and error-prone network is of crucial importance for the service providers. Therefore, it is of fundamental importance to analyse the impact of the network impairments and video content on perceived quality during the QoE metric design. The major contributions of the article are in the study of i)the impact of network impairments together with video content, ii) impact of the video content and ii) the impact of video content related parameters: spatial-temporal perceptual information, video content, and frame size on QoE has been presented. The results show that when the impact of impairments on perceived quality is low, the quality is significantly influenced by video content, and video content itself also has a significant impact on QoE. Finally, the results strengthen the need for new parameter characterization, for better QoE metric design.

Characterization and selection of light field content for perceptual assessment

Light field technology may have a positive impact on several multimedia applications thanks to novel ways to explore the captured scenes, such as changing the parallax (horizontally and vertically) and refocusing the content. These innovative use cases require new considerations that affect the whole processing chain, from content acquisition to visualization, as well as the methodologies for quality evaluation. In particular, capturing and selecting the appropriate content is crucial for a successful development and evaluation of audiovisual technologies. Thus, this paper presents a framework addressing the reconsideration of the space of attributes for an adequate characterization of light field data. Firstly, an exhaustive characterization of light field content is described, based on various particular features, including depth and refocusing properties to traditional spatial, temporal, and color indicators. Then, based on this characterization, specific techniques are proposed for an effective selection of light field content for perceptual quality assessment.

Distortion-based no-reference quality metric for video transmission over IP

No-reference video quality assessment is a challenging task since the quality evaluation is not based on a priori knowledge of the original signal. In this paper we propose a no-reference quality metric for IP-based video transmission. The video quality is estimated based on the evaluation of the artifacts introduced by H.264/AVC coding and by the impairments caused by the IP transmission system. Performance experiments show the effectiveness of the proposed system in matching the subjective judgment. The collected scores have been compared with state of art video quality metrics.