Adaptive Mobile Video Delivery Based on Fountain Codes and DASH:A Survey

Recent years have witnessed an explosive growth in mobile video-based services and efficient and reliable video delivery draws more and more attention. As a type of rateless codes, fountain codes can automatically adapt to wireless channel conditions with- out any knowledge of channels. This paper provides an overview of several typical Foi-ward Error Correction （FEC） codes, such as Reed-Solomon （RS） code, Tornado code, Luby-Transform （LT） code, and Raptor code. We focus on a novel delay-aware fountain coding （DAF） technique that maxinfizes the code word length under the constraint of a given delay. Based on DAF, this paper also presents Unequal Error Protection DAF （UEP-DAF） which improves the Peak Signal to Noise Ratio （PSNR） without additional co- ordination between the encoder and the decoder, as well as Model Predictive Control DAF （MPC-DAF） which reduces the compu- tational complexity to an affordable level for real-time video comnmnications. Moreover, we review- video streaming technologies, then introduce Dynamic Adaptive Streaming over HTTP （DASH） and DASH over Multiple Content Distribution Servers （MCDS- DASH） in detail. Based on MCDS-DASH that adapts video bitrate at the block level to alleviate video fluctuation, we propose a novel approach to integrating fountain codes with MCDS-DASH, which is capable of achieving unprecedented high throughput.

Robust Watermarking of Mobile Video Resistant against Barrel Distortion

In head mounted display(HMD),in order to cancel pincushion distortion,the images displayed on the mobile should be prewarped with barrel distortion.The copyright of the mobile video should be verified on both the original view and the pre-warped virtual view.A robust watermarking resistant against barrel distortion for HMDs is proposed in this paper.Watermark mask is embedded into image in consideration of imperceptibility and robustness of watermarking.In order to detect watermark from the pre-warped image with barrel distortion,an estimation method of the barrel distortion is proposed for HMDs.Then,the same warp is enforced on the embedded watermark mask with the estimated parameters of barrel distortion.The correlation between the warped watermark and the pre-warped image is computed to predicate the existence of watermark.As shown in experimental results,watermark of mobile video can be detected not only from the original views,but also from the pre-warped virtual view.It also shows that the proposed scheme is resistant against combined barrel distortion and common post-processing,such as JPEG compression.

Efficient Video Transmission in D2D Assisted Mobile Cloud Networks

The increasing popularity of smart mobile devices and the rise of online services has increased the requirements for efficient dissemination of social video contents. In this paper,we study the problem of distributing video from cloud server to users in partially connected cooperative D2 D network using network coding. In such a scenario, the transmission conflicts occur from simultaneous transmissions of multiple devices, and the scheduling decision should be made not only on the encoded packets but also on the set of transmitting devices. We analyze the lower bound and give an integer linear formulation of the joint optimization problem over the set of transmitting devices and the packet combinations.We also propose a heuristic solution for this setup using a conflict graph and local graph at every device. Simulation results show that our coding scheme significantly reduces the number of transmission slots, which will increase the efficiency of video delivery.

Enabling QoE-aware Mobile Cloud Video Recording over Roadside Vehicular Networks

Most of previous video recording devices in mobile vehicles commonly store captured video contents locally. With the rapid development of 4G/Wi Fi networks, there emerges a new trend to equip video recording devices with wireless interfaces to enable video uploading to the cloud for video playback in a later time point. In this paper, we propose a QoE-aware mobile cloud video recording scheme in the roadside vehicular networks, which can adaptively select the proper wireless interface and video bitrate for video uploading to the cloud. To maximize the total utility, we need to design a control strategy to carefully balance the transmission cost and the achieved QoE for users. To this purpose, we investigate the tradeoff between cost incurred by uploading through cellular networks and the achieved QoE of users. We apply the optimization framework to solve the formulated problem and design an online scheduling algorithm. We also conduct extensive trace-driven simulations and our results show that our algorithm achieves a good balance between the transmission cost and user QoE.

Research on Information Architecture Design of Short-Form Video Social Platforms Based on Cognitive Psychology

This study investigates how cognitive psychology principles can be integrated into the information architecture design of short-form video platforms,like TikTok,to enhance user experience,engagement,and sharing.Using a questionnaire,it explores TikTok users’habits and preferences,highlighting how social media fatigue(SMF)impacts their interaction with the platform.The paper offers strategies to optimize TikTok’s design.It suggests refining the organizational system using principles like chunking,schema theory,and working memory capacity.Additionally,it proposes incorporating shopping features within TikTok’s interface to personalize product suggestions and enable monetization for influencers and content creators.Furthermore,the study underlines the need to consider gender differences and user preferences in improving TikTok’s sharing features,recommending streamlined and customizable sharing options,collaborative sharing,and a system to acknowledge sharing milestones.Aiming to strengthen social connections and increase sharing likelihood,this research provides insights into enhancing information architecture for short-form video platforms,contributing to their growth and success.

Sports video summarization and adaptation for application in mobile communication

Sports video appeals to large audiences due to its high commercial potentials. Automatically extracting useful semantic information and generating highlight summary from sports video to facilitate users' accessing requirements is an important problem, especially in the forthcoming broadband mobile communication and the need for users to access their multimedia information of interest from anywhere at anytime with their most convenient digital equipments. A system to generate highlight summaries oriented for mobile applications is introduced, which includes highlight extraction and video adaptation. In this system, several highlight extraction techniques are provided for field sports video and racket sports video by using multi-modal information. To enhance users' viewing experience and save bandwidth, 3D animation from highlight segment is also generated. As an important procedure to make video analysis results universally applicable, video transcoding techniques are applied to adapt the video for mobile communication environment and user preference. Experimental results are encouraging and show the advantage and feasibility of the system for multimedia content personalization, enhancement and adaptation to meet different user preference and network/device requirements.

Joint Content Placement and Traffic Management for Cloud Mobile Video Distribution over Software-Defined Networks

To cope with the rapid growth of mobile video, video providers have leveraged cloud technologies to deploy their mobile video service system for more cost-effective and scalable performance. The emergence of Software-Defined Networking(SDN) provides a promising solution to manage the underlying network. In this paper, we introduce an SDN-enabled cloud mobile video distribution architecture and propose a joint video placement, request dispatching and traffic management mechanism to improve user experience and reduce the system operational cost. We use a utility function to capture the two aspects of user experience: the level of satisfaction and average latency, and formulate the joint optimization problem as a mixed integer programming problem. We develop an optimal algorithm based on dual decomposition and prove its optimality. We conduct simulations to evaluate the performance of our algorithm and the results show that our strategy can effectively cut down the total cost and guarantee user experience.

Evaluate mobile video quality with LTE radio access network parameters

To evaluate the video quality, we tested sample videos delivered using HTTP adaptive streaming （HAS） in LTE network. In order to establish a correlation between radio access network （RAN） performance and quality of experience （ QoE）, we set up a testbed under different radio im- pairment conditions with three parameters： signal to interference and noise ratio （ SINR）, an amount of available network resource and a round trip latency. End users graded each video in a mobile equipment with their QoE Mearnwhile, we used a nonlinear model to simulate the comprehensive pre- dicted mean opinion score （pMOS）. Our results show that the nonlinear model can predict the enduser＇ s feedback. The pearson correlation coefficient （PCC） of the model is larger than 0. 9. This demonstrate that the output of the model has a high correlation with the end users＇ ratings and can reflect the QoE accurately. The method we developed will help mobile network operators evaluate the RAN performance of its QoE. It can also be used for HAS service to optimize LTE network and improve its QoE.

H.264/AVC error resilience tools suitable for 3G mobile video services

The emergence of third generation mobile system (3G) makes video transmission in wireless environment possible, and the latest 3GPP/3GPP2 standards require 3G terminals support H.264/AVC. Due to high packet loss rate in wireless envi- ronment, error resilience for 3G terminals is necessary. Moreover, because of the hardware restrictions, 3G mobile terminals support only part of H.264/AVC error resilience tool. This paper analyzes various error resilience tools and their functions, and presents 2 error resilience strategies for 3G mobile streaming video services and mobile conversational services. Performances of the proposed error resilience strategies were tested using off-line common test conditions. Experiments showed that the proposed error resilience strategies can yield reasonably satisfactory results.

Next Generation Mobile Video Networking

HWANG Jenq-Neng received his Ph.D. degree from the University of Southern California, USA. In the summer of 1989, Dr. HWANG joined the De- partment of Electrical Engineering of the Universi- ty of Washington in Seattle, USA, where he has been promoted to Full Professor since 1999. He served as the Associate Chair for Research fi＇om 2003 to 2005, and from 2011-2015. He is current- ly the Associate Chair for Global Affairs and Inter- national Development in the EE Depamnent. Hehas written more than 330 journal papers, conference papers and book chapters in the areas of machine learning, muhimedia signal processing, and muhimedia system integration and networking, including an au- thored textbook on ＂Multimedia Networking： from Theory to Practice,＂ published by Cambridge University Press. Dr. HWANG has close work- ing relationship with the industry on muhimedia signal processing and nmltimedia networking.

Intelligent Mobile Video Surveillance System with Multilevel Distillation

This paper proposes a mobile video surveillance system consisting of intelligent video analysis and mobile communication networking. This multilevel distillation approach helps mobile users monitor tremendous surveillance videos on demand through video streaming over mobile communication networks. The intelligent video analysis includes moving object detection/tracking and key frame selection which can browse useful video clips. The communication networking services, comprising video transcoding, multimedia messaging, and mobile video streaming, transmit surveillance information into mobile appliances. Moving object detection is achieved by background subtraction and particle filter tracking. Key frame selection, which aims to deliver an alarm to a mobile client using multimedia messaging service accompanied with an extracted clear frame, is reached by devising a weighted importance criterion considering object clarity and face appearance. Besides, a spatial- domain cascaded transcoder is developed to convert the filtered image sequence of detected objects into the mobile video streaming format. Experimental results show that the system can successfully detect all events of moving objects for a complex surveillance scene, choose very appropriate key frames for users, and transcode the images with a high power signal-to-noise ratio （PSNR）.

Network＇ Video Display：索尼VoIP网络视频电话系统PCS-G50＆IVE Mobile Service

VoIP（Video over Internet protocol）是一种新型的语音通话技术。它能将语音压缩打包然后透过互联网传送，在目前成熟的宽带环境中其实现成本，通话质量以及媒体多元融合特性都远远抛离了传统电话，

基于Windows Mobile的移动视频监控系统

提出了一个基于Windows Mobile的移动视频监控系统设计方案.介绍了整个视频监控系统的体系结构,讨论了在移动平台上实现视频监控的相关关键技术,重点阐述了移动视频监控系统的实现.测试结果及系统实际应用效果证明了该设计方案的有效性.

基于Windows Mobile的移动视频监控系统

提出一个基于Windows Mobile的移动视频监控系统设计方案。文章介绍了整个视频监控系统的体系结构,讨论了在移动平台上实现视频监控的相关关键技术,重点阐述了移动视频监控系统的实现。测试结果及系统实际应用效果证明了该设计方案的有效性。

基于MobileNet的移动端城管案件目标识别算法

针对目前大量安装的固定监控摄像头存在监控死角,以及移动设备硬件性能较低等问题,提出一种可在较低性能的IOS移动设备上运行的城市管理案件目标识别算法。首先,在MobileNet中增加新的超参数,优化输入输出图像的通道数与每个通道所产生的特征图数量;随后,将改进后的MobileNet与SSD目标识别框架相结合构成一种新的识别算法,并移植到IOS移动端设备上;最后,该算法利用移动端设备自带的摄像头拍摄案发现场视频,实现对8种特定城管案件目标的准确检测。该算法检测结果的平均精度均值(mAP)与原型YOLO和原型SSD相比,分别提升了15.5个百分点和10.4个百分点。实验结果表明,所提算法可以在低性能IOS移动设备上流畅运行,减少了监控死角,为城管队员加速案件分类与处理提供了技术支撑。

基于PhoneGap和jQuery Mobile的移动校园WebApp的研究与实现

本文以广东松山职业技术学院移动校园系统建设为例,利用PhoneGap技术开发一个跨平台WebApp系统。项目小组通过对学院内师生的调研分析出了该系统的功能,设计了满足师生需要的功能模块;系统在开发模式上采用了MVC的设计模式,利用PhoneGap+jQuery Mobile+AJAX+HTML5+Servlet+MySql等技术搭建开发架构。论文对跨域数据交换、视频播放等问题,提出解决方案,最终做到开发一个Web项目,能够得到"一个网站,两个App"的设计成果。

Prototyping and Evaluating a Wearable System for Mobile Distributed Collaboration

We have developed a wearable system for mobile distributed collaboration called HandsInAir using emerging wireless and mobile technologies. This system was developed to support real world scenarios in which a remote mobile helper guides a local mobile worker in the completion of a physical task. HandsInAir consists of a helper unit and a worker unit. Both units are equipped with wearable devices having the same hardware configuration, but running different pieces of software to support the distinct roles of the collaborators (helper and worker). The two sides are connected via a wireless network and the collaboration partners can communicate with each other via audio and visual links. In this paper we describe the technical implementation of the system and present a preliminary evaluation of it. The paper concludes with a brief discussion of possible future work for further improvements and new developments.

Medical Image Compression Method Using Lightweight Multi-Layer Perceptron for Mobile Healthcare Applications

As video compression is one of the core technologies required to enable seamless medical data streaming in mobile healthcare applications,there is a need to develop powerful media codecs that can achieve minimum bitrates while maintaining high perceptual quality.Versatile Video Coding(VVC)is the latest video coding standard that can provide powerful coding performance with a similar visual quality compared to the previously developed method that is High Efficiency Video Coding(HEVC).In order to achieve this improved coding performance,VVC adopted various advanced coding tools,such as flexible Multi-type Tree(MTT)block structure which uses Binary Tree(BT)split and Ternary Tree(TT)split.However,VVC encoder requires heavy computational complexity due to the excessive Ratedistortion Optimization(RDO)processes used to determine the optimalMTT block mode.In this paper,we propose a fast MTT decision method with two Lightweight Neural Networks(LNNs)using Multi-layer Perceptron(MLP),which are applied to determine the early termination of the TT split within the encoding process.Experimental results show that the proposed method significantly reduced the encoding complexity up to 26%with unnoticeable coding loss compared to the VVC TestModel(VTM).

Wireless ad hoc video transmission:a Bayesian network-based scheme

A novel bandwidth prediction and control scheme is proposed for video transmission over an ad boc network. The scheme is based on cross-layer, feedback, and Bayesian network techniques. The impacts of video quality are formulized and deduced. The relevant factors are obtained by a cross-layer mechanism or Feedback method. According to these relevant factors, the variable set and the Bayesian network topology are determined. Then a Bayesian network prediction model is constructed. The results of the prediction can be used as the bandwidth of the mobile ad hoc network （MANET）. According to the bandwidth, the video encoder is controlled to dynamically adjust and encode the right bit rates of a real-time video stream. Integrated simulation of a video streaming communication system is implemented to validate the proposed solution. In contrast to the conventional transfer scheme, the results of the experiment indicate that the proposed scheme can make the best use of the network bandwidth; there are considerable improvements in the packet loss and the visual quality of real-time video.K

MEC-Assisted Flexible Transcoding Strategy for Adaptive Bitrate Video Streaming in Small Cell Networks

Adaptive bitrate video streaming(ABR)has become a critical technique for mobile video streaming to cope with time-varying network conditions and different user preferences.However,there are still many problems in achieving high-quality ABR video streaming over cellular networks.Mobile Edge Computing(MEC)is a promising paradigm to overcome the above problems by providing video transcoding capability and caching the ABR video streaming within the radio access network(RAN).In this paper,we propose a flexible transcoding strategy to provide viewers with low-latency video streaming services in the MEC networks under the limited storage,computing,and spectrum resources.According to the information collected from users,the MEC server acts as a controlling component to adjust the transcoding strategy flexibly based on optimizing the video caching placement strategy.Specifically,we cache the proper bitrate version of the video segments at the edge servers and select the appropriate bitrate version of the video segments to perform transcoding under jointly considering access control,resource allocation,and user preferences.We formulate this problem as a nonconvex optimization and mixed combinatorial problem.Moreover,the simulation results indicate that our proposed algorithm can ensure a low-latency viewing experience for users.