Our demonstration highlights the use of semantic communication to transmit stereo frame streams and its application in immersive media. Considering the limitations of traditional stereo compression with digital transmission under poor channel conditions, such as the cliff effect and high latency in computation and transmission, we employ the Deep Joint Source and Channel Coding (Deep JSCC) framework to transmit semantic information of stereo streams between the sender and receiver. To address channel instability, we propose a dynamic rate adjustment method that adapts to channel conditions while maintaining transmission efficiency and reconstruction quality. Furthermore, we extend this work to stereo stream applications, enabling the real-time synthesis of multiple novel view streams of the streamer. The overall design of this demo enables an immersive multi-view experience by transmitting rate-controlled semantic features from only two perspectives.

The surge in popularity of live video streaming has spurred the development of various bitrate adaptation techniques, all aimed at enhancing user Quality of Experience (QoE). Compared to streaming Video-on-Demand, achieving low-latency live video streaming under fluctuating network conditions poses additional challenges. It requires finding the balance between rebuffering avoidance and latency, as a small client buffer is required to achieve low latency. Video players can also employ playback speed control to help optimize this balance. Specifically, when client buffer occupancy is high and hence latency is high, the player may increase playback speed to reduce the latency; and conversely, when client buffer occupancy is low and hence the risk of rebuffering is high, the player may reduce playback speed to increase buffer occupancy. Based on this rationale, a variety of playback speed control methods have been proposed. This paper evaluates, using a real-world testbed, the effectiveness of various playback speed control mechanisms when applied to a set of bitrate adaptation algorithms, with the evaluation also encompassing variations in target latency and network conditions. Our findings show a lack of coordination between adaptive bitrate (ABR) algorithms and playback speed control mechanisms. This leads us to conclude that there is a need for new playback speed control methods designed in conjunction with ABR algorithms.

HTTP Adaptive Streaming (HAS), the most prominent technology for streaming video over the Internet, suffers from high end-to-end latency when compared to conventional broadcast methods. This latency is caused by the content being delivered as segments rather than as a continuous stream, requiring the client to buffer significant amounts of data to provide resilience to variations in network throughput and enable continuous playout of content without stalling. The client uses an Adaptive Bitrate (ABR) algorithm to select the quality at which to request each segment to trade-off video quality with the avoidance of stalling to improve the Quality of Experience (QoE). The speed at which the ABR algorithm responds to changes in network conditions influences the amount of data that needs to be buffered, and hence to achieve low latency the ABR needs to respond quickly. Llama (Lyko et al. 28) is a new low latency ABR algorithm that we have previously proposed and assessed against four on-demand ABR algorithms. In this article, we report an evaluation of Llama that demonstrates its suitability for low latency streaming and compares its performance against three state-of-the-art low latency ABR algorithms across multiple QoE metrics and in various network scenarios. Additionally, we report an extensive subjective test to assess the impact of variations in video quality on QoE, where the variations are derived from ABR behaviour observed in the evaluation, using short segments and scenarios. We publish our subjective testing results in full and make our throughput traces available to the research community.

Increasingly, major live events are being delivered using HTTP Adaptive Streaming (HAS), which, being a unicast technology, causes such events to generate huge traffic demand peaks on broadband networks which in turn drive significant investment in the network to increase capacity. Multicast ABR (mABR) is a streaming technology that inserts multicast into the path of a unicast HAS stream, allowing the traffic peaks to be reduced while requiring little or no change to the client players. But the unmodified clients continue to behave as HAS clients, asynchronously requesting content segments, adapting the quality of content requested according to perceived network conditions, totally unaware of the use of multicast to deliver synchronously one or more of the available encoded representations of the content to a local proxy. This creates inefficiencies and challenges in system design. Segments delivered synchronously must be cached locally ready for asynchronous requests from the client. Adaptation by the client will cause unwanted segments to be received by multicast, and alternative representations to be requested by unicast. We exploit CDN log data for BT Sport channels delivered by HAS to explore these inefficiencies and challenges. We show that unicast traffic in the core network could be reduced by more than 75% by delivering a single HAS representation by multicast to each client proxy, with larger savings for HD than UHD streams. We show that a cache at the client proxy capable of storing seven segments of 6s duration would be sufficient to be able to satisfy the majority of asynchronous requests from clients. Finally, we evaluate the performance of four policies for a client proxy to join and leave multicast groups in terms of the competing metrics of savings in unicast traffic in the core network and the quantity of data delivered over the access network.

Point cloud geometry (PCG) is used to precisely represent arbitrary-shaped 3D objects and scenes, is of great interest to vast applications which puts forward the pressing desire of high-efficiency PCG compression for transmission and storage. Existing PCG coding mostly relies on the octree model by which point-wise processing is applied without exploring nonlocal regional geometry similarity across the entire 3D surface. This work, instead, suggests the region-wise processing to leverage the region similarity to exploit inter-region redundancy for efficient lossy point cloud geometry compression. Towards this goal, a given PCG is first segmented into numerous local regions each of which comprises a portion of point cloud surface, and can be represented by a surface vector that describes the geometry shape numerically in a projected principal space. Subsequently, these regions are grouped into several discriminative clusters, assuring that inter-cluster similarity is minimized and intra-cluster similarity is maximized simultaneously, where the similarity is calculated using the regional surface vectors. In each cluster, we set a reference region having the largest similarity score to the others, which enables the non-reference region prediction from the reference one using alignment transform. In the end, we encode the reference regions directly using the lossless mode of the Geometry-based Point Cloud Compression (G-PCC), while corresponding non-reference regions are signaled using associated transform parameters. Compared with the state-of-the-art G-PCC using octree model, our region-wise approach can offer remarkable coding efficiency improvement, e.g., 32.4% and 22.0% Bjontegaard-delta rate (BD-Rate) gains for respective point-to-point (D1) and point-to-plane (D2) distortion evaluations, across a variety of common test sequences used in standard committee.

HTTP Adaptive Streaming (HAS) technologies such as MPEG DASH are now used extensively to deliver television services to large numbers of viewers. In HAS, the client requests segments of content using HTTP, with an ABR algorithm selecting the quality at which to request each segment to trade-off video quality with the avoidance of stalling. This introduces significant end to end latency compared to traditional broadcast, due to the the client requiring a large enough buffer for the ABR algorithm to react to changes in network conditions in a timely manner. The recently standardised Common Media Application Format (CMAF) has helped address the issue of latency by defining segments as composed of independently transferable chunks. In this paper, we describe a simulation model we have developed to evaluate the performance of four popular ABR algorithms using DASH and CMAF in various low latency live streaming scenarios. Realistic network conditions are used for the evaluation, which are based on throughput data taken from the CDN logs of a commercial live TV service. We quantify the performance of the ABR algorithms using a selection of QoE metrics, and show that CMAF can significantly improve ABR performance in low delay scenarios.

In the recent years, HTTP Adaptive Bit Rate (ABR) streaming including Dynamic Adaptive Streaming over HTTP (DASH) has become the most popular technology for video streaming over the Internet. The client device requests segments of content using HTTP, with an ABR algorithm selecting the quality at which to request each segment to trade-off video quality with the avoidance of stalling. This introduces high latency compared to traditional broadcast methods, mostly in the client buffer which needs to hold enough data to absorb any changes in network conditions. Clients employ an ABR algorithm which monitors network conditions and adjusts the quality at which segments are requested to maximise the user's Quality of Experience. The size of the client buffer depends on the ABR algorithm's capability to respond to changes in network conditions in a timely manner, hence, low latency live streaming requires an ABR algorithm that can perform well with a small client buffer. In this paper, we present Llama a new ABR algorithm specifically designed to operate in such scenarios. Our new ABR algorithm employs the novel idea of using two independent throughput measurements made over different timescales. We have evaluated Llama by comparing it against four popular ABR algorithms in terms of multiple QoE metrics, across multiple client settings, and in various network scenarios based on CDN logs of a commercial live TV service. Llama outperforms other ABR algorithms, improving the P.1203 Mean Opinion Score (MOS) as well as reducing rebuffering by 33% when using DASH, and 68% with CMAF in the lowest latency scenario.

In this paper we describe a subjective test we have performed with 60 viewers over the age of 18 and 570 young students, the majority being 10 or 11 years old, to understand the relative annoyance caused by various transmission impairments when viewing television content. We wanted to compare errors associated with broadcast and multicast delivery which appear as areas of extreme color or tearing of the image, with errors associated with Adaptive Bit Rate unicast, such as interruptions and quality variations. We also wanted to study the impact of the type of screen the content is viewed on, considering viewing on tablets and on a TV. We have found a significant level of consistency over all of the results we have collected. Interruptions were the most annoying impairment, with multiple short interruptions being more annoying than a single longer one, and with missing content being more annoying than simply pausing. We found more tolerance to quality variation on tablets, and found that younger adults are more annoyed by impairments on tablets and older adults more annoyed when watching on the TV. We have found the young students to have similar views to the adults, and have found them to be capable of participating in subjective tests.

For expanded coverage of this month’s topic “Evolving Distribution,” you can find the following paper in the Digital Edition. Visit the SMPTE digital library at http://journal.smpte.org to access the issue and to read this additional paper.

Adaptive bit rate streaming using HTTP delivery is now widely used to provide live audio-visual content services. However, the quality of experience is often considered inferior to that of conventional broadcast services due to the high end to end latency, which is mostly due to the large amount of buffering required to provide resilience to variable network conditions. In this paper we present our initial research to address this issue of high latency. If each segment of content could be delivered in a consistent period of time, the amount of buffering required could be reduced. We present the results of simulations where we have changed the timing of the TCP congestion response to consider the timing requirements of content segments, while trying to retain fairness to competing flows. We show that with this simple modification to TCP the variation in the delivery time of content segments can be reduced and much lower end to end latency achieved. With no changes to the network or client devices required, this solution may be straightforward to deploy to make the user experience of streaming services much closer to that of conventional broadcast services.

In this paper we describe a set of video subjective tests with 498 student viewers in the age range 9-17. These tests are based on earlier tests that we carried out with adult viewers. The aim was not to validate our earlier results, but to use them as a reference against which we could compare the scores of the students, to allow us to address the questions of how sensitive students in this age range are to video quality issues, and how suitable they would be as viewers in subjective tests. We used the same test content as in our earlier tests, including content at high and ultra-high resolution, and with standard and high dynamic range.

This paper describes of a set of subjective tests that the authors have carried out to assess the end user perception of video encoded with High Dynamic Range technology when viewed in a typical home environment.Viewers scored individual single clips of content, presented in High Definition (HD) and Ultra High Definition (UHD), in Standard Dynamic Range (SDR), and in High Dynamic Range (HDR) using both the Perceptual Quantizer (PQ) and Hybrid Log Gamma (HLG) transfer characteristics, and presented in SDR as the backwards compatible rendering of the HLG representation.The quality of SDR HD was improved by approximately equal amounts by either increasing the dynamic range or increasing the resolution to UHD. A further smaller increase in quality was observed in the Mean Opinion Scores of the viewers by increasing both the dynamic range and the resolution, but this was not quite statistically significant.

Content-Centric Networks have been designed for the shift in the focus of the Internet from being a point-to-point IP network to a Content Store-and-Forward network based on naming the content, not the location. Requesting by name, rather than location allows content caching to be integrated as a fundamental part of the network infrastructure. This paper projects a future with a Tele-Content provider based on a Content-Centric Network infrastructure, and shows how the links between users, applications, and service providers change to support this new type of network infrastructure.

Content Delivery Networks are commonplace in today’s Internet and are an important technique in the distribution of multimedia content to the plethora of Internet Protocol enabled devices. However, it has been recognised that current networks are many times over provisioned server side for peak demand and therefore greatly under utilised at other times. The emergence of cloud computing as a commercial reality has created the opportunity where content delivery networks can leverage the resources of existing cloud providers to increase capacity when required. In this paper, we propose an Elastic Video Endpoint (EVE), a virtualised multimedia distribution resource, which can utilise cloud resources to dynamically provision capacity in real time. Initial results have shown that the system can respond to increased load and provide extra bandwidth capacity on demand. Keywords-cloud; elastic; content delivery network; dynamic provisioning.

A field trial of Quality driven Video Streaming is described and shows how we can achieve approximately a 40% reduction in byte volume for adaptive constant quality delivery compared to adaptive constant bitrate delivery while maintaining the equivalent overall quality. The trials were carried out over BT's broadband network.