Multipath routing and rate-controlled video encoding in wireless video surveillance networks

Video surveillance systems typically consist of many video sources distributed over a wide area, transmitting live video streams to a central location for processing and monitoring. The target of this paper—to bring down the overall system cost and increase feasibility, scalability, and performance—is to propose a new architecture for a wireless video surveillance network, whose telecommunication infrastructure is based on a wireless mesh network, and where video sources are able to estimate network bandwidth and consequently control their output rate. Multipath routing is applied in such a way that at least part of the information arrives at its destination even if a wireless link is shielded (maliciously or not). A case study is considered to discuss the performance of the proposed architecture, analyzing a comparison between single-path and multipath approaches.     

一种网络视频监控系统的专用存储方案

针对网络视频监控系统中传统文件系统存储方案存储效率低和检索性能差的缺陷,提出一种基于裸磁盘设备的录像存储方案。根据监控系统的数据存储特点,采用B＋树管理录像段索引信息,设计一种磁盘逻辑存储结构,并给出一种基于图像组的数据缓存机制。系统测试结果表明,与传统的文件系统存储方案相比,该方案在监控系统的512Kb／s和1Mb／s典型存储码率下,录像存储效率分别提高了43．6％和30．3％,录像检索耗时降至35ms以下。     

Content-aware rate allocation for efficient video streaming via dynamic network utility maximization

Nowadays it is vital to design robust mechanisms to provide QoS for multimedia applications as an integral part of the network traffic. The main goal of this paper is to provide an efficient rate control scheme to support content-aware video transmission mechanism with buffer underflow avoidance at the receiver in congested networks. Towards this, we introduce a content-aware time-varying utility function, in which the quality impact of video content is incorporated into its mathematical expression. Moreover, we analytically model the buffer requirements of video sources in two ways: first as constraints of the optimization problem to guarantee a minimum rate demand for each source, and second as a penalty function embedded as part of the objective function attempting to achieve the highest possible rate for each source. Then, using the proposed analytical model, we formulate a dynamic network utility maximization problem, which aims to maximize the aggregate hybrid objective function of sources subject to capacity and buffer constraints. Finally, using primal–dual method, we solve DNUM problem and propose a distributed algorithm called CA-DNUM that optimally allocates the shared bandwidth to video streams. The experimental results demonstrate the efficacy and performance improvement of the proposed content-aware rate allocation algorithm for video sources in different scenarios.     

Joint Video Coding and Statistical Multiplexing for Broadcasting Over DVB-H Channels

A novel joint video encoding and statistical multiplexing (StatMux) method for broadcasting over digital video broadcasting for handhelds (DVB-H) channels is proposed to improve the quality of encoded video and to decrease the end-to-end delay in a broadcast system. The main parts of end-to-end delay in a DVB-H system result from a time-sliced transmission scheme that is used in DVB-H and from the bit rate variations of service bit streams. The time-sliced transmission scheme is utilized in DVB-H to reduce the power consumption of DVB-H receivers. Variable bit rate (VBR) video bit streams are used in DVB-H to improve the video quality and compression performance. The time-sliced transmission scheme has increased the channel switching delay, i.e., switching to a new audio-visual service, in DVB-H. The used VBR bit streams increase the required buffering delays in the whole system. The different parts of end-to-end delay in a DVB-H system can be affected by the used video encoding and multiplexing methods. Different scenarios for encoding and StatMux of video sources for DVB-H application are studied in this paper. Moreover, a new method for jointly encoding and StatMux of video sources is proposed that not only decreases the end-to-end delay but also improves the average quality of compressed video by dynamically distributing available bandwidth between the video sources according to their relative complexity. Performance of the proposed method is validated by simulation results.      

基于MPEG视频流的动态带宽分配算法

ATM是兴起的宽带网标准,基于报文的视频正是宽带网上的一个典型应用.变位率视频的传输方法为恒定的视频质量提供了可能,但是在传输过程中,报文的丢失、延迟和延迟抖动等因素都会影响视频质量,因此有必要提供QoS保证.提出了两种新的在ATM网上进行MPEG视频传输的动态带宽分配算法,一种是动态计算算法,另一种是动态虚拟缓存算法.在这些算法中,根据允许的丢包率,动态地调整MPEG视频带宽以保证QoS.     

Reducing channel zapping time in live TV broadcasting over content centric networks

Channel zapping delay is a big challenge in delivering TV service over the Internet infrastructure. Previous research works have studied this delay, its components, and solutions to decrease it. Unfortunately, the best proposed solutions reduce the delay at the expense of increasing bandwidth usage or decreasing the received video quality. After channel switching, the Set Top Box (STB) or player application should buffer sufficient frames before starting to play the received video. However, the buffering process takes place at the playback rate and leads to a delay which is inversely related to the buffer duration. Regarding Information Centric Networking (ICN) paradigm, this paper introduces a new channel zapping protocol that aims to remove the synchronization and buffering delays while maintaining the bandwidth utilization and also the received video quality. The general idea of the proposed solution is to exploit the in-network caching feature of the ICN to retrieve the frames from the network at the network speed. Although the analyses show that the proposed zapping protocol eliminates the delay dependency to the buffer duration, network throughput becomes the bottleneck instead. So, novel solutions have been proposed to reduce the queuing delay as the main component of network delay. These solutions include two new caching algorithms, a new cache replacement algorithm, and applying scheduling methods to the forwarding queues. Simulation results show that increasing link rates, using the proposed caching and cache replacement algorithms, and applying an appropriate scheduling method will greatly reduce the zapping delay without sacrificing the bandwidth or video quality.     

“全球眼”视频监控系统服务质量监测研究

全球眼网络视频监控业务是电信最重要的增值服务之一,其中最关键的环节是服务质量的保证。对视频质量监测的常用方法进行研究,提出了一套针对全球眼系统的视频质量监测的方案。该方案通过在网络层检测获得关键节点的网络状况,定位故障发生的位置;在应用层监测在视频终端进行图像质量分析,监测黑场、静帧和马赛克等错误的发生。随着多个监控点的数据汇集到告警服务器,系统可以即时发布故障报告。     

The interleaved video frame distribution for P2P-based VoD system with VCR functionality

The peer-to-peer (P2P) network structure is widely employed for video streaming applications because of its high stability, flexible extensibility, and ability to distribute data stream loading among different peer nodes. Numerous P2P schemes have been proposed for video on demand (VoD) applications. High video source searching cost and long response latency are always issues in dealing with VCR functionality, such as jump and fast-forward/rewind, because of asynchronous interactive and random join/leave behaviors of end users. To overcome this bottleneck, an interleaved video frame distribution (IVFD) scheme is proposed to support full VCR functionality in a P2P environment without searching for new sources. Instead of acquiring video stream data from a single parent peer in the published schemes, each child peer in the IVFD scheme can simultaneously acquire interleaved video data from multiple parent peers. When a client peer carries out arbitrary VCR operations, such as jump or fast-forward/rewind, its parent peers are still able to provide intermittent video stream data for the client peer; thus, no video source search is necessary. Simulation results reveal excellent load distribution performance and response latency for VCR operations in the proposed IVFD scheme.     

An adaptable neural-network model for recursive nonlinear traffic prediction and modeling of MPEG video sources

Multimedia services and especially digital video is expected to be the major traffic component transmitted over communication networks [such as internet protocol (IP)-based networks]. For this reason, traffic characterization and modeling of such services are required for an efficient network operation. The generated models can be used as traffic rate predictors, during the network operation phase (online traffic modeling), or as video generators for estimating the network resources, during the network design phase (offline traffic modeling). In this paper, an adaptable neural-network architecture is proposed covering both cases. The scheme is based on an efficient recursive weight estimation algorithm, which adapts the network response to current conditions. In particular, the algorithm updates the network weights so that 1) the network output, after the adaptation, is approximately equal to current bit rates (current traffic statistics) and 2) a minimal degradation over the obtained network knowledge is provided. It can be shown that the proposed adaptable neural-network architecture simulates a recursive nonlinear autoregressive model (RNAR) similar to the notation used in the linear case. The algorithm presents low computational complexity and high efficiency in tracking traffic rates in contrast to conventional retraining schemes. Furthermore, for the problem of offline traffic modeling, a novel correlation mechanism is proposed for capturing the burstness of the actual MPEG video traffic. The performance of the model is evaluated using several real-life MPEG coded video sources of long duration and compared with other linear/nonlinear techniques used for both cases. The results indicate that the proposed adaptable neural-network architecture presents better performance than other examined techniques.     

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

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.     

视频服务器网络中影像对象映射问题的研究

视频服务器网络中的影像对象映射问题是一种新的组合优化问题.服务器网络可以建立在基于局域网的工作站网络之上,也可以建立在广域网之上.基于对用户的服务请求模式、服务器网络的存储容量和通信带宽等因素的综合考虑,研究了服务器网络中影像对象映射问题,利用局部搜索算法给出了一套对该映射问题的解决方案.然后用一套基准集实例对给出的算法集进行验证.结果表明,在较短的计算时间内,该算法可以得到近似最优解的方案.     

Enhancing aggregate QoS for video streaming

The IETF's Differentiated Services architecture is designed to provide different types or levels of service for Internet traffic. One of its key features is that traffic flows are aggregated so that routers in the core network only need to distinguish a relatively small number of aggregate flows, even if those flows consist of hundreds or thousands of individual flows. However, network-level QoS differentiation may not satisfy the requirements of many QoS-sensitive applications such as live video streaming, where end-to-end delay and reliability must be guaranteed.

This paper investigates application-level service differentiation for MPEG video streaming in a Diff-Serv-aware MPLS network infrastructure, along with routing support at the network layer. Based on the fact that MPEG video has become one of the most popular formats for Internet (wired and wireless) users, our approach enhances aggregate QoS for video streaming by employing existing application-level knowledge of the MPEG video structure; therefore it requires neither a new video compression algorithm nor additional bandwidth. Several MPEG video dispersion models are proposed and analyzed. Simulation results show that two such strategies are superior to the other tested. In addition, a new routing scheme is proposed to support searching the ‘best’ paths for efficient multi-path video streaming. Through extensive simulations, we demonstrate that our approaches improve the aggregate QoS of MPEG video streams, as well as overall network efficiency.     

An incentive scheduling mechanism for peer-to-peer video streaming

P2P video streaming networks are found as a scalable solution and an alternative for traditional client–server based video streaming over the Internet. One of the significant issues affecting the success of any P2P streaming network is cooperation between peers. Practical observations have proved the prevalence of free riders in P2P networks that degrade their performance. To solve this problem, using incentive mechanisms, which encourage peers to contribute more in the network, is necessary. In this paper, we designed and proposed a distributed and scalable incentive mechanism for mesh based P2P video streaming networks. In the proposed approach the contribution of the peers is measured and maintained in a distributed fashion. Furthermore, we proposed an incentive sending side scheduler in which peers are served based on their contribution in the network. Our simulation evaluations show the efficiency of the proposed approach in improving the overall perceived video quality by the non-free rider nodes and consequently in the whole network.     

On the source switching problem of Peer-to-Peer streaming

Peer-to-Peer(P2P) streaming has been proved a popular and efficient paradigm of Internet media streaming. In some applications, such as an Internet video distance education system, there are multiple media sources which work alternately. A fundamental problem in designing such kind of P2P streaming system is how to achieve fast source switching so that the startup delay of the new source can be minimized. In this paper, we propose an efficient solution to this problem. We model the source switch process, formulate it into an optimization problem and derive its theoretical optimal solution. Then we propose a practical greedy algorithm, named fast source switch algorithm, which approximates the optimal solution by properly interleaving the data delivery of different media sources. The algorithm can adapt to the dynamics and heterogeneity of real Internet environments. We have carried out extensive simulations on various real-trace P2P overlay topologies to demonstrate the effectiveness of our model and algorithm. The simulation results show that our proposed algorithm outperforms the normal source switch algorithm by reducing the source switch time by 20%–30% without bringing extra communication overhead. The reduction in source switching time is more obvious as the network scale increases.     

Video multimodal emotion recognition based on Bi-GRU and attention fusion

A video multimodal emotion recognition method based on Bi-GRU and attention fusion is proposed in this paper. Bidirectional gated recurrent unit (Bi-GRU) is applied to improve the accuracy of emotion recognition in time contexts. A new network initialization method is proposed and applied to the network model, which can further improve the video emotion recognition accuracy of the time-contextual learning. To overcome the weight consistency of each modality in multimodal fusion, a video multimodal emotion recognition method based on attention fusion network is proposed. The attention fusion network can calculate the attention distribution of each modality at each moment in real-time so that the network model can learn multimodal contextual information in real-time. The experimental results show that the proposed method can improve the accuracy of emotion recognition in three single modalities of textual, visual, and audio, meanwhile improve the accuracy of video multimodal emotion recognition. The proposed method outperforms the existing state-of-the-art methods for multimodal emotion recognition in sentiment classification and sentiment regression.

     

Packet loss resilience using unequal forward error correction assignment for video transmission over communication networks

Forward error correction (FEC) methods have been developed for packet loss resilience in application layer for real-time video transmission over communication networks. In this paper, an efficient packet loss resilience method is proposed using closed form solution for unequal FEC assignment based on a new packet distortion model. We first derive the packet distortion model by investigating the error concealment property and error propagation effect in H.264. To select the source and channel rate minimizing the overall distortion, we present a model-based rate allocation algorithm using the packet distortion model and rate-distortion function. Then we propose the closed form solution for unequal FEC assignment, which uses the packet distortion model and considers channel status information. Simulation results show that the proposed method gives substantial improvement for the received video quality in packet-lossy Internet and wireless network environments, while it requires much less computational complexity compared to the previous scheme.     

A new technique for minimizing network loss from users’ perspective

Loss control is an essential issue for video transportation over IP networks. Buffer management is a traditional network technique to protecting video data against IP packet loss. In this paper, a new innovative use of packet scheduling to meet the loss constraints of video communication is proposed. A packet-scheduling scheme at a router that assures that intra and inter-stream loss requests for video transportation are met was developed and evaluated using real video data. The results demonstrate the advantages of the proposed scheme, in terms of loss performance and fairness.     

基于流媒体服务的视频监控系统设计

本文提出一种基于流媒体服务的视频监控系统方案。采用流媒体服务机制，在现有C／S模式的视频监控系统基础上，通过部署流媒体服务器．在多个用户并发访问同一路视频信号时，始终保证在流媒体和前端编码器链路上，只有一份数据拷贝在网络中传输，最大限度减小冗余数据包．提高数据传输效率．避免大容量的视频数据传输引起的网络拥塞。     

基于多协议融合的实时移动视频监控系统

提出一种支持多协议融合的实时视频监控系统的设计与实现方案.系统可通过 Hi3520嵌入式处理器平台和移动端摄像头进行视频采集,采用H.264/AVC压缩编码和参数优化,兼容RTP/RTSP和RTMP多种通信协议进行媒体流传输;设计的Android的移动客户端可以实现视频数据的实时解析、网络串流等.实验测试表明： PC和采集端显示的画面仅有1~1.5秒延迟,系统可以灵活实现不同应用场景下的高清、实时监控.     

基于DaVinci技术的3G移动视频监控系统设计与实现

本文针对3G移动视频监控系统面临实时性高、运算量大、带宽低的要求,提出了一种基于DaVinci技术和3G网络传输为基础的解决方案。该方案完成了系统硬件详细设计和软件模块化详细设计,实现了OSD字幕的前端添加功能,并解决了在3G无线带宽抖动下采用自适应帧码率和QoS机制,使视频图像流畅稳定。本设计的测试结果表明,能够在3G低带宽下流畅地进行移动视频监控。