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Gaming video streaming services have grown tremendously in the past few years, with higher resolutions, higher frame rates and HDR gaming videos getting increasingly adopted among the gaming community. Since gaming content as such is different from non-gaming content, it is imperative to evaluate the performance of the existing encoders to help understand the bandwidth requirements of such services, as well as further improve the compression efficiency of such encoders. Towards this end, we present in this paper GamingHDRVideoSET, a dataset consisting of eighteen 10-bit UHD-HDR gaming videos and encoded video sequences using four different codecs, together with their objective evaluation results. The dataset is available online at [to be added after paper acceptance]. Additionally, the paper discusses the codec compression efficiency of most widely used practical encoders, i.e., x264 (H.264/AVC), x265 (H.265/HEVC) and libvpx (VP9), as well the recently proposed encoder libaom (AV1), on 10-bit, UHD-HDR content gaming content. Our results show that the latest compression standard AV1 results in the best compression efficiency, followed by HEVC, H.264, and VP9., 14 pages, 8 figures, submitted to IEEE journal

While industry has adopted blockchain-based video-streaming platforms, other stakeholders could contribute more to grow the technology and support its implementation. This article reviews current blockchain-based video streaming applications and industrial advancements and identifies today's research activities and future opportunities for investigation.

The streaming of gaming content, both passive and interactive, has increased manifolds in recent years. Gaming contents bring with them some peculiarities which are normally not seen in traditional 2D videos, such as the artificial and synthetic nature of contents or repetition of objects in a game. In addition, the perception of gaming content by the user is different from that of traditional 2D videos due to its pecularities and also the fact that users may not often watch such content. Hence, it becomes imperative to evaluate whether the existing video quality models usually designed for traditional 2D videos are applicable to gaming content. In this paper, we evaluate the applicability of the recently standardized bitstream-based video-quality model ITU-T P.1204.3 on gaming content. To analyze the performance of this model, we used 4 different gaming datasets (3 publicly available + 1 internal) not previously used for model training, and compared it with the existing state-of-the-art models. We found that the ITU P.1204.3 model out of the box performs well on these unseen datasets, with an RMSE ranging between 0.38 − 0.45 on the 5-point absolute category rating and Pearson Correlation between 0.85 − 0.93 across all the 4 databases. We further propose a full-HD variant of the P.1204.3 model, since the original model is trained and validated which targets a resolution of 4K/UHD-1. A 50:50 split across all databases is used to train and validate this variant so as to make sure that the proposed model is applicable to various conditions.

With the increasing demand in video traffic, delivering appropriate Quality of Experience may appear as a challenge for highly popular services such as Twitch.tv and YouTube-Gaming. This paper presents the evaluation of three widely used encoders, namely H.264, H.265 and AV1, for the case of gaming videos, assuming streaming scenario. The performance of the codecs has been assessed in terms of objective video quality metrics (PSNR, SSIM and VMAF) and subjective video quality assessment. The encoding settings were kept similar for all the three aforementioned encoders. In the considered setting, AV1 achieves a better level of video quality both in terms of objective and subjective VQA, for almost all bitrates and content considered. The improvement is remarkable in particular for the lower range of bitrates considered.

Existing works in the field of quality assessment focus separately on gaming and non-gaming content. Along with the traditional modeling approaches, deep learning based approaches have been used to develop quality models, due to their high prediction accuracy. In this paper, we present a deep learning based quality estimation model considering both gaming and non-gaming videos. The model is developed in three phases. First, a convolutional neural network (CNN) is trained based on an objective metric which allows the CNN to learn video artifacts such as blurriness and blockiness. Next, the model is fine-tuned based on a small image quality dataset using blockiness and blurriness ratings. Finally, a Random Forest is used to pool frame-level predictions and temporal information of videos in order to predict the overall video quality. The light-weight, low complexity nature of the model makes it suitable for real-time applications considering both gaming and non-gaming content while achieving similar performance to existing state-of-the-art model NDNetGaming. The model implementation for testing is available on GitHub1.

Subjective tests for the assessment of the quality of experience (QoE) are typically run with a pool of subjects providing their opinion scores using a 5-point scale. The subjects’ mean opinion score (MOS) is generally assumed as the best estimation of the average score in the target population. Indeed, for a large enough sample, we may assume that the mean of the variations across the subjects approaches zero, but this is not the case for the limited number of subjects typically considered in subjective tests. In this paper, we propose an approach based on generalized linear models (GLMs) for estimation of the population average QoE. The motivating dataset is composed of the individual scores assigned by 25 subjects to a set of gaming videos evaluated under different resolutions and compression ratios. The approach recognizes the multinomial nature of the data and allows for correlation between scores of the same subject. The resulting estimated average QoE is shown to follow more credible patterns than the MOS, particularly for higher bitrates, for which the model estimates present more coherent behavior. Similar convincing results are found on a second dataset, showing the validity of the approach.

Recently, streaming of gameplay scenes has gained much attention, as evident with the rise of platforms such as Twitch.tv and Facebook Gaming. These streaming services have to deal with many challenges due to the low quality of source materials caused by client devices, network limitations such as bandwidth and packet loss, as well as low delay requirements. Spatial video artifact such as blockiness and blurriness as a result of as video compression or up-scaling algorithms can significantly impact the Quality of Experience of end-users of passive gaming video streaming applications. In this paper, we investigate solutions to enhance the video quality of compressed gaming content. Recently, several super-resolution enhancement techniques using Generative Adversarial Network (e.g., SRGAN) have been proposed, which are shown to work with high accuracy on non-gaming content. Towards this end, we improved the SRGAN by adding a modified loss function as well as changing the generator network such as layer levels and skip connections to improve the flow of information in the network, which is shown to improve the perceived quality significantly. In addition, we present a performance evaluation of improved SRGAN for the enhancement of frame quality caused by compression and rescaling artifacts for gaming content encoded in multiple resolution-bitrate pairs.

We provide in this paper a tutorial and a comprehensive survey of QoE management solutions in current and future networks. We start with a high level description of QoE management for multimedia services, which integrates QoE modelling, monitoring, and optimization. This followed by a discussion of HTTP Adaptive Streaming (HAS) solutions as the dominant technique for streaming videos over the best-effort Internet. We then summarize the key elements in SDN/NFV along with an overview of ongoing research projects, standardization activities and use cases related to SDN, NFV, and other emerging applications. We provide a survey of the state-of-the-art of QoE management techniques categorized into three different groups: a) QoE-aware/driven strategies using SDN and/or NFV; b) QoE-aware/driven approaches for adaptive streaming over emerging architectures such as multi-access edge computing, cloud/fog computing, and information-centric networking; and c) extended QoE management approaches in new domains such as immersive augmented and virtual reality, mulsemedia and video gaming applications. Based on the review, we present a list of identified future QoE management challenges regarding emerging multimedia applications, network management and orchestration, network slicing and collaborative service management in softwarized networks. Finally, we provide a discussion on future research directions with a focus on emerging research areas in QoE management, such as QoE-oriented business models, QoE-based big data strategies, and scalability issues in QoE optimization., Comment: 42 pages, 21 figures, 10 tables

Gaming as a popular system has recently expanded the associated services, by stepping into live streaming services. Live gaming video streaming is not only limited to cloud gaming services, such as Geforce Now, but also include passive streaming, where the players' gameplay is streamed both live and ondemand over services such as Twitch.tv and YouTubeGaming. So far, in terms of gaming video quality assessment, typical video quality assessment methods have been used. However, their performance remains quite unsatisfactory. In this paper, we present a new No Reference (NR) gaming video quality metric called NR-GVQM with performance comparable to state-of-the-art Full Reference (FR) metrics. NR-GVQM is designed by training a Support Vector Regression (SVR) with the Gaussian kernel using nine frame-level indexes such as naturalness and blockiness as input features and Video Multimethod Assessment Fusion (VMAF) scores as the ground truth. Our results based on a publicly available dataset of gaming videos are shown to have a correlation score of 0.98 with VMAF and 0.89 with MOS scores. We further present two approaches to reduce computational complexity.

Gaming video streaming has become increasingly popular in recent times. Along with the rise and popularity of cloud gaming services and e-sports, passive gaming video streaming services such as Twitch.tv, YouTubeGaming, etc. where viewers watch the gameplay of other gamers, have seen increasing acceptance. Twitch.tv alone has over 2.2 million monthly streamers and 15 million daily active users with almost a million average concurrent users, making Twitch.tv the 4th biggest internet traffic generator, just after Netflix, YouTube and Apple. Despite the increasing importance and popularity of such live gaming video streaming services, they have until recently not caught the attention of the quality assessment research community. For the continued success of such services, it is imperative to maintain and satisfy the end user Quality of Experience (QoE), which can be measured using various Video Quality Assessment (VQA) methods. Gaming videos are synthetic and artificial in nature and have different streaming requirements as compared to traditional non-gaming content. While there exist a lot of subjective and objective studies in the field of quality assessment of Video-on-demand (VOD) streaming services, such as Netflix and YouTube, along with the design of many VQA metrics, no work has been done previously towards quality assessment of live passive gaming video streaming applications. The research work in this thesis tries to address this gap by using various subjective and objective quality assessment studies. A codec comparison using the three most popular and widely used compression standards is performed to determine their compression efficiency. Furthermore, a subjective and objective comparative study is carried out to find out the difference between gaming and non-gaming videos in terms of the trade-off between quality and data-rate after compression. This is followed by the creation of an open source gaming video dataset, which is then used for a performance evaluation study of the eight most popular VQA metrics. Different temporal pooling strategies and content based classification approaches are evaluated to assess their effect on the VQA metrics. Finally, due to the low performance of existing No-Reference (NR) VQA metrics on gaming video content, two machine learning based NR models are designed using NR features and existing NR metrics, which are shown to outperform existing NR metrics while performing on par with state-of-the-art Full-Reference (FR) VQA metrics.

Video Quality assessment is imperative to estimate and hence manage the Quality of Experience (QoE) in video streaming applications to the end-user. Recent years have seen a tremendous advancement in the field of objective video quality assessment (VQA) metrics, with the development of models that can predict the quality of the videos streamed over the Internet. However, no work so far has attempted to study the performance of such quality assessment metrics on gaming videos, which are artificial and synthetic and have different streaming requirements than traditionally streamed videos. Towards this end, we present in this paper a study of the performance of objective quality assessment metrics for gaming videos considering passive streaming applications. Objective quality assessment considering eight widely used VQA metrics is performed on a dataset of 24 reference videos and 576 compressed sequences obtained by encoding them at 24 different resolution-bitrate pairs. We present an evaluation of the performance behavior of the VQA metrics. Our results indicate that VMAF predicts subjective video quality ratings the best, while NIQE turns out to be a promising alternative as a no-reference metric in some scenarios.

Excited state proton transfer (ESPT) of an anionic photoacid 8-hydroxypyrene-1,3,6-trisulfonic acid (HPTS or pyranine) has been studied inside a cationic reverse micelle (RM), water/benzylhexadecyldimethylammonium chloride (BHDC)/benzene, using steady-state and time-resolved fluorescence spectroscopy. The observed ESPT behavior is found to be remarkably different from the known ESPT trend of HPTS inside anionic AOT and cationic CTAB RMs; the ESPT dynamics approaches that of bulk water at higher w0 (≥10) inside AOT RM while no ESPT was observed for CTAB reverse micelle [ Sedgwick J. Am. Chem. Soc. 2012 , 134 , 11904 - 11907 ]. The ESPT dynamics inside BHDC RM is remarkably slower compared to that of water at all w0 (= [water]/[surfactant]) values and relatively much less sensitive to w0 variation compared to AOT RM. 2D NOESY and fluorescence anisotropy measurements reveal that the probe (HPTS) is embedded inside the positive interface of BHDC RM. Despite its trapped location, HPTS is able to undergo ESPT due to significant penetration of water molecules into the interface. Furthermore, facile ESPT at higher w0 is consistent with higher degree of interface hydration as predicted by a recent MD simulation [ Agazzi Langmuir 2014 , 30 , 9643 - 9653 ]. The study shows that ESPT dynamics inside RM varies not only with the interface charge but also on the nature of the headgroup and solvation.

Recently, we demonstrated that the fluorescence of coumarin 102 (C102) drastically quenches upon hydrogen bonding (H-bonding) with phenol in a non-polar solvent cyclohexane due to H-bond driven photoinduced electron transfer (PET) (J. Phys. Chem. A, 2013, 117, 3945–3953). However, the work was limited to low concentrations of phenol only, where predominately a 1 : 1 C102–phenol complex exists. Herein, we report an unusual fluorescence modulation of C102 over mole fractions of the H-bond donor (phenol) in the cyclohexane–phenol mixtures covering a higher range of mole fractions. We found that the fluorescence quantum yield (ϕf) and fluorescence lifetime (τf) of C102 first diminish steadily with increase in the concentration of phenol, but after a particular mole fraction (XPhOH = 0.013) both the quantities (ϕf and τf) increase upon further increase in the phenol content. The results can be attributed to the competitive nature of the C102–phenol and the phenol–phenol H-bonding. Since the PET quenching operates through the H-bond between the CO group of C102 and the HO– group of phenol, the H-bond may fail to attain an optimum geometry when the phenol is linked with other phenols via the H-bond. The variation of the C102–phenol H-bonding nature with the mole fraction of phenol was supplemented by FT-IR measurements. Similar unusual variation of the C102 fluorescence is observed in the phenol–anisole mixtures to a lesser extent, but is completely absent in the anisole–cyclohexane mixtures, where H-bonding is practically impossible.

Nanoparticle synthesis within reverse micelle core has exceptional control over size and morphology. The aqueous core (water pool) acts as a nanoreactor supporting chemical reduction of metal salts, while a layer of surfactant molecules (interfacial layer) casing the water pool serves as a template to halt the growth up to a specific size. Because of the soft nature of the interfacial layer (template), the grown nanoparticles may severely influence the structural organization of the original reverse micelle. Here, using a site-selective hydrophilic probe, coumarin 343 (C343), we have characterized the interfacial layer of water/sodium dioctylsulfosuccinate (AOT)/n-heptane reverse micelles before and after silver nanoparticle (AgNP) formation by combination of steady-state absorption, excitation, emission spectroscopy, time-resolved fluorescence anisotropy, and dynamic Stokes shift measurements. We found that both solvation dynamics and rotational dynamics inside the interfacial region of the reverse micel...

Despite intensive research, the role of the H-bonding environment on ultrafast PET remains illusive. For example, coumarin 153 (C153) undergoes ultrafast photoinduced electron transfer (PET) in electron-donating solvents, in both aniline (AN) and N,N-dimethylaniline (DMA), despite their very different H-bonding abilities. Thus, donor-acceptor (AN-C153) H-bonding may have only a minor role in PET (Yoshihara and co-workers, J. Phys. Chem. A, 1998, 102, 3089). However, donor-acceptor H-bonding may be somehow less effective in the neat H-bonding environment but could become dominant in the presence of an inert solvent (Phys. Chem. Chem. Phys., 2014, 16, 6159). We successfully applied and tested the proposal here. The nature of PET modulation of C153 in the presence of a passive component cyclohexane is found to be very different for aniline and DMA. Upon addition of cyclohexane to DMA, the PET process gradually becomes retarded but in the case of AN, the PET rate was indeed found to be accelerated at some intermediate composition (mole fraction of aniline, XAN∼ 0.74) compared to that of neat aniline. It is intuitive that cyclohexane may replace some of the donors (AN or DMA) from the vicinity of the acceptor and, thus, should disfavour PET. However, in the hydrogen bonding environment using molecular dynamics simulation, for the first time, we show that the average number of aniline molecules orienting their N-H group in the proximity of the C=O group of C153 is actually higher at the intermediate mole fraction (0.74) of aniline in a mixture rather than in neat aniline. This small but finite excess of C153-AN H-bonding already present in the ground state may possibly account for the anomalous effect. The TD-DFT calculations presented here showed that the intermolecular H-bonding between C153 and AN strengthens from 21.1 kJ mol(-1) in the ground state to 33.0 kJ mol(-1) in the excited state and, consequently, H-bonding may assist PET according to the Zhao and Han model. Thus, we not only justified both the theoretical prediction (efficient H-bond assisted PET within the C153-AN pair) and experimental observation (minor H-bond assisted PET in neat solvent) but also established our previous hypothesis that an inert co-solvent can enhance the effect of H-bonding from molecular insights.

In a previous study, we reported a striking observation that photoinduced electron transfer (PET) from aniline (AN) to photoexcited coumarin 102 (C102) can be accelerated by adding an inert component (cyclohexane or toluene) to the neat electron donor solvent AN (Phys. Chem. Chem. Phys., 2014, 16, 6159–6166). The H-bond linking the electron donor (D, AN) and the acceptor (A, C102) was proposed to dictate the PET process. To account for the unusual variation of quenching pattern with AN mole fraction, two possible reasons were cited – (1) the D–A (AN–C102) H-bonding may be modulated due to change in polarity of the medium or (2) the additional D–D (AN–AN) H-bonding may restrain the D–A H-bonding to adjust optimally for the PET. Here, we investigate the PET of C102 in an AN–dimethylaniline (DMA) mixture to negate the polarity variation. Since, both AN and DMA have similar polarities, the polarity of the mixture should remain invariant at all compositions. Nevertheless, we found that the fluorescence quantum yield and lifetime of C102 in the mixtures follows a similar unusual trend as observed earlier in the AN–toluene or AN–cyclohexane mixtures; it first decreases up to a particular mole fraction (XD) of the H-bond donor AN and, thereafter, increases on further enrichment of the donor. The observed PET modulation may be rationalized by considering efficient PET in the 1 : 1 H-bonded C102–AN complex but less efficient PET in higher order C102–(AN)n≥2 complexes, where additional D–D (AN–AN) H-bonding may influence the key C102–AN H-bonding and thus inhibit the PET process.

In a neat electron-donating solvent (in this case aniline), photoinduced electron transfer (PET) from the solvent to an excited acceptor (e.g. a coumarin fluorophore) may be anticipated to be the most efficient because of the close contact of the acceptor with many donors. Addition of an inert component would most likely retard the PET process by replacing some donors from the neighbourhood of the acceptors. Surprisingly, we found dramatic acceleration of PET (6–10 fold enhancement compared to neat aniline), for coumarin 102 (C102) dissolved in a binary mixture of aniline and an inert solvent (cyclohexane or toluene). The PET induced fluorescence follows an anomalous trend against the mole fraction of aniline (XAN); first quenches up to certain XAN (0.075 for cyclohexane; 0.13 for toluene), thereafter, enhances with increase in XAN. Although the non-interacting component cannot directly participate in the PET process, it may modulate C102–aniline H-bonding association by changing the polarity of the medium or by disrupting the aniline–aniline H-bond. The study clearly illustrates the dominant role of hydrogen bonding in activating the electron transfer rate where standard thermodynamics predicts very weak donor–acceptor interaction.

We report a convenient synthesis of silver nanoparticles (AgNPs) using ascorbic acid (AA) as a reducing agent in sodium dioctylsulfosuccinate (AOT) reverse micelles at w0 (=[water]/[AOT]) values of 2, 6 and 10. Simple injection of silver nitrate and AA solutions into AOT/n-heptane mixtures leads to formation of nanoparticles at room temperature in the absence of inert atmosphere or prolonged stirring. The optical quality of the surface plasmon resonance (SPR) band of the synthesized AgNPs was found to be superior (stronger peak and narrower bandwidth) than for AgNPs obtained by common reducing agents like sodium borohydride or hydrazine under similar conditions. Transmission electron microscopy (TEM) and dynamic light scattering (DLS) measurements revealed that the nanoparticles are spherical, and are slightly larger than the pure reverse micelles. Also, the size and the polydispersity increase with increase in the w0 value.

The fate of intermolecular hydrogen bond (H-bond) upon electronic excitation of a H-bonded complex has been debated in literature. For a model H-bonded complex, coumarin 102 (C102)-phenol in a noninteracting solvent ethylene tetrachloride, time-resolved infrared spectroscopy experiment of Nibbering and coworkers suggests that the H-bond between the C102 and phenol ruptures upon electronic excitation (C. Chudoba et al. J. Phys. Chem. A1999, 103, 5625-5628). On the contrary, Zhao and Han have demonstrated for the first time that the intermolecular hydrogen bond is significantly strengthened, while not disrupted, in the electronically excited states of the hydrogen-bonded complexes upon electronic excitation using the time-dependent density functional theory method (G. J. Zhao and K. L. Han J. Phys. Chem. A2007, 111, 2469-2474). The two excited-state hydrogen bonding dynamics mechanisms have widely different predictions of the emission or electronic relaxation of the excited H-bonded complex. The excited-state hydrogen-bond strengthening mechanism proposed by Zhao and Han anticipates a stronger intermolecular interaction, while the H-bond breaking mechanism speculates no interaction between C102 and phenol. The speculation has been tested here on the same system (H-bonded C102-phenol complex) in another noninteracting solvent cyclohexane. We found a strong quenching of the C102 emission in the H-bonded complex. Selectively excited (λex = 405 nm) H-bonded complex relaxes on a fast time scale of 400-600 ps and may be attributed to the conversion of the locally excited (LE) state to a nonfluorescent charge transfer (CT) state assisted by the strong excited-state H-bond formation. A minor component (∼10%) of 2.5 to 1.8 ns is ascribed to the LE complex without a H-bond. The findings are in accordance with the new fluorescence quenching mechanism that the excited-state intermolecular hydrogen bond strengthening facilitates CT from phenol to coumarin in the excited state (G. J. Zhao et al. J. Phys. Chem. B2007, 111, 8940-8945). Fluorescence quenching was absent for anisole, where H-bond formation is not possible and was more pronounced for p-Cl-phenol, where even stronger H-bonding is expected.