A no-reference blocking artifact metric for B-DCT video

A new no-reference blocking artifact metric for B-DCT compression video is presented in this paper. We first present a new definition of blocking artifact and a new method for measuring perceptive blocking artifact based on HVS taking into account the luminance masking and activity masking characteristic. Then, we propose a new concept of blocking artifact cluster and the algorithm for clustering blocking artifacts. Considering eye movement and fixation, we select several clusters with most serious blocking artifacts and utilize the average of their blocking artifacts to assess the total blocking artifact of B-DCT reconstructed video. Experimental results illustrating the performance of the proposed method are presented and evaluated.

A Novel Objective Quality Assessment Method for Video Conferencing Coding

Most recently, due to the demand of immersive communication, region-of-interest-based(ROI) high efficiency video coding(HEVC) approaches in conferencing scenarios have become increasingly important. However, there exists no objective metric, specially developed for efficiently evaluating the perceived visual quality of video conferencing coding. Therefore, this paper proposes a novel objective quality assessment method, namely Gaussian mixture model based peak signal-tonoise ratio(GMM-PSNR), for the perceptual video conferencing coding. First, eye tracking experiments, together with a real-time technique of face and facial feature extraction, are introduced. In the experiments, importance of background, face, and facial feature regions is identified, and it is then quantified based on eye fixation points over test videos. Next, assuming that the distribution of the eye fixation points obeys Gaussian mixture model, we utilize expectation-maximization(EM) algorithm to generate an importance weight map for each frame of video conferencing coding, in light of a new term eye fixation points/pixel(efp/p). According to the generated weight map, GMM-PSNR is developed for quality assessment by assigning different weights to the distortion of each pixel in the video frame. Finally, we utilize some experiments to investigate the correlation of the proposed GMM-PSNR and other conventional objective metrics with subjective quality metrics. The experimental results show the effectiveness of GMM-PSNR.

Network video quality assessment based on fuzzy inference system

The objective assessment method of network video quality is a challenge, because the video quality will be distorted by various factors, including transmission and compression. In order to improve the objective method, an objective assessment method based on fuzzy inference system of Mamdani is proposed. Firstly, six quality parameters are introduced. All the quality parameters are inputted to fuzzy logic controller system. Secondly, the outputs are used as next inputs and inferred by another fuzzy logic controller system to obtain the objective quality of network video. Lastly, the performance of proposed method is validated on four videos with different network environment. Meanwhile this method is compared with other methods. The experimental results show that the proposed method can improve the similarity between subjective and objective assessment.

Beyond Video Quality:Evaluation of Spatial Presence in 360-Degree Videos

With the rapid development of immersive multimedia technologies,360-degree video services have quickly gained popularity and how to ensure sufficient spatial presence of end users when viewing 360-degree videos becomes a new challenge.In this regard,accurately acquiring users’sense of spatial presence is of fundamental importance for video service providers to improve their service quality.Unfortunately,there is no efficient evaluation model so far for measuring the sense of spatial presence for 360-degree videos.In this paper,we first design an assessment framework to clarify the influencing factors of spatial presence.Related parameters of 360-degree videos and headmounted display devices are both considered in this framework.Well-designed subjective experiments are then conducted to investigate the impact of various influencing factors on the sense of presence.Based on the subjective ratings,we propose a spatial presence assessment model that can be easily deployed in 360-degree video applications.To the best of our knowledge,this is the first attempt in literature to establish a quantitative spatial presence assessment model by using technical parameters that are easily extracted.Experimental results demonstrate that the proposed model can reliably predict the sense of spatial presence.

Video classification for video quality prediction

In this paper we propose a novel method for video quality prediction using video classification. In essence, our ap- proach can serve two goals: (1) To measure the video quality of compressed video sequences without referencing to the original uncompressed videos, i.e., to realize No-Reference (NR) video quality evaluation; (2) To predict quality scores for uncompressed video sequences at various bitrates without actually encoding them. The use of our approach can help realize video streaming with ideal Quality of Service (QoS). Our approach is a low complexity solution, which is specially suitable for application to mobile video streaming where the resources at the handsets are scarce.

Recent Advances and Challenges of Visual Signal Quality Assessment

While quality assessment is essential for testing, optimizing, benchmarking, monitoring, and inspecting related systems and services, it also plays an essential role in the design of virtually all visual signal processing and communication algorithms, as well as various related decision-making processes. In this paper, we first provide an overview of recently derived quality assessment approaches for traditional visual signals (i.e., 2D images/videos), with highlights for new trends (such as machine learning approaches). On the other hand, with the ongoing development of devices and multimedia services, newly emerged visual signals (e.g., mobile/3D videos) are becoming more and more popular. This work focuses on recent progresses of quality metrics, which have been reviewed for the newly emerged forms of visual signals, which include scalable and mobile videos, High Dynamic Range (HDR) images, image segmentation results, 3D images/videos, and retargeted images.

QI-BRiCE: Quality Index for Bleeding Regions in Capsule Endoscopy Videos

With the advent in services such as telemedicine and telesurgery,provision of continuous quality monitoring for these services has become a challenge for the network operators.Quality standards for provision of such services are application specic as medical imagery is quite different than general purpose images and videos.This paper presents a novel full reference objective video quality metric that focuses on estimating the quality of wireless capsule endoscopy(WCE)videos containing bleeding regions.Bleeding regions in gastrointestinal tract have been focused in this research,as bleeding is one of the major reasons behind several diseases within the tract.The method jointly estimates the diagnostic as well as perceptual quality of WCE videos,and accurately predicts the quality,which is in high correlation with the subjective differential mean opinion scores(DMOS).The proposed combines motion quality estimates,bleeding regions’quality estimates based on support vector machine(SVM)and perceptual quality estimates using the pristine and impaired WCE videos.Our method Quality Index for Bleeding Regions in Capsule Endoscopy(QI-BRiCE)videos is one of its kind and the results show high correlation in terms of Pearson’s linear correlation coefcient(PLCC)and Spearman’s rank order correlation coefcient(SROCC).An F-test is also provided in the results section to prove the statistical signicance of our proposed method.

Evaluation of packet loss impairment on streaming video

Video compression technologies are essential in video streaming application because they could save a great amount of network resources. However compressed videos are also extremely sensitive to packet loss which is inevitable in today's best effort IP network. Therefore we think accurate evaluation of packet loss impairment on compressed video is very important. In this work, we develop an analytic model to describe these impairments without the reference of the original video (NR) and propose an impairment metric based on the model, which takes into account both impairment length and impairment strength. To evaluate an impaired frame or video, we design a detection and evaluation algorithm (DE algorithm) to compute the above metric value. The DE algorithm has low computational complexity and is currently being implemented in the real-time monitoring module of our HDTV over IP system. The impairment metric and DE algorithm could also be used in adaptive system or be used to compare diffeient error concealment strategies.

Suitability of VVC and HEVC for Video Telehealth Systems

Video compression in medical video streaming is one of the key technologies associated with mobile healthcare.Seamless delivery of medical video streams over a resource constrained network emphasizes the need of a video codec that requires minimum bitrates and maintains high perceptual quality.This paper presents a comparative study between High Efciency Video Coding(HEVC)and its potential successor Versatile Video Coding(VVC)in the context of healthcare.A large-scale subjective experiment comprising of twenty-four non-expert participants is presented for eight different test conditions in Full High Denition(FHD)videos.The presented analysis highlights the impact of compression artefacts on the perceptual quality of HEVC and VVC processed videos.Our results and ndings show that VVC clearly outperforms HEVC in terms of achieving higher compression,while maintaining high quality in FHD videos.VVC requires upto 40%less bitrate for encoding an FHD video at excellent perceptual quality.We have provided rate-quality curves for both encoders and a degree of overlap across both codecs in terms of perceptual quality.Overall,there is a 71%degree of overlap in terms of quality between VVC and HEVC compressed videos for eight different test conditions.

Automated neurosurgical video segmentation and retrieval system

Medical video repositories play important roles for many health-related issues such as medical imaging, medical research and education, medical diagnostics and training of medical professionals. Due to the increasing availability of the digital video data, indexing, annotating and the retrieval of the information are crucial. Since performing these processes are both computationally expensive and time consuming, automated systems are needed. In this paper, we present a medical video segmentation and retrieval research initiative. We describe the key components of the system including video segmentation engine, image retrieval engine and image quality assessment module. The aim of this research is to provide an online tool for indexing, browsing and retrieving the neurosurgical videotapes. This tool will allow people to retrieve the specific information in a long video tape they are interested in instead of looking through the entire content.

基于GMSL2的智能驾驶域控制器视频输出功能检测系统研究

智能驾驶域控制器承担着处理和分析来自各种传感器的数据。然而,随着车载摄像头数量的不断增加,域控制器内部的解串,加串,图像处理等各个环节都可能出现丢帧和像素异常问题,进而对其图像处理结果产生负面影响。为了精准评估智能驾驶域控制器的GMSL2视频输出功能,研究了一种双路GMSL2视频采集和视频质量对比系统。通过硬件板卡设计将GMSL2接口视频信号解串为MIPI CSI-2信号,由桥接芯片MC20901将MIPI CSI-2信号分离为FPGA可识别的LVDS信号和CMOS信号。通过XLINX XC7K325T-FFG900主控芯片进行FPGA逻辑设计,实现MIPI信号解析,YUV422转RGB888视频格式转码,DDR3缓存和PCIe 2.0×8总线上传。最后,以6位数码管百分秒表和24色标准色卡为拍摄对象,将拍摄到的视频帧结合图像特征提取、数码管穿线识别算法和RGB加权欧几里得色差公式,实现视频的丢帧和色差检测。实验结果表明:本系统能够实时采集双路YUV422 8 bit、4K、30 fps的GMSL2接口视频数据,并对智能驾驶域控制器输出的视频是否存在丢帧和色差问题进行定量分析,区分出被测件合格品与不合格品。提高了智能驾驶域控制视频输入输出功能检测结果的可靠性。

基于ResNet-TSM和BiGRU网络的移动视频感知质量评价模型

考虑到卡顿、质量切换、内容特征等因素对用户体验质量的影响都会直接体现在客户端的失真视频里,提出了一种客户端的移动视频感知质量评价模型。该模型无须对每种影响因素均进行表征和度量,而是基于深度特征提取+回归的思路,直接建立失真视频与平均意见分数之间的映射模型。首先,构建了ResNet-TSM网络结构,提取失真视频片段的深度时空特征;为了避免维度灾难,采用LargeVis算法对提取的深度特征进行降维,同时提升特征的表达与区分能力。然后,采用双向门控循环单元网络对视频的长时间依赖关系进行建模,得到各视频片段的打分,再利用时间平均池化方法将各片段分数进行聚合,得到整个视频的打分结果。在WaterlooSQoE-Ⅲ和LIVE-NFLX-Ⅱ数据集上的实验结果表明,提出的模型可以获得更高的预测精度。

基于视频理解的教学过程感知与分析

课堂是教育教学的核心阵地,对教师在课堂上的教学环节进行过程化监测和评价是提高课堂教学质量的有效途径。然而,现有基于人工的评价模式存在评价效率低下、易干扰课堂教学、主观误差等缺点,难以达到理想的效果。鉴于人工智能技术的快速发展,提出将以人为中心的智能感知与分析技术引入教师的教学过程中,对教师主体进行实时识别与分析。首先,通过人脸检测算法定位教师实时位置并进行位移分析;其次,利用视线估计算法对教师的关注区域进行检测;最后,采用基于骨架点的动作识别和表情识别对教师的动作和表情进行感知与分析。同时,对指标进行量化统计,以更为高效、客观地了解教师的教学特点,从而帮助教师针对性地改善其授课质量。在相同配置环境下的实验结果表明,该系统的各模块在相应任务中的表现较好,符合教学场景下的使用要求。从在真实的教学视频上的测试结果来看,所设计的系统能够较为准确地感知教师的教学状态,为提升授课质量提供建设性意见。

基于逆向重建和运动轨迹偏移的视频重定向质量评价

随着视频重定向方法的日渐发展,对视频重定向质量客观评价算法的要求愈高。现存的视频重定向质量客观评价算法均以Scale Invariant Feature Transform flow(SIFT-flow)稠密匹配为基础。当原始帧与重定向帧尺寸不一致时,SIFT-flow稠密匹配会产生错误,客观评价算法性能下降。在匹配过程中,逆向重建网格存在未匹配区域。基于上述情况,提出一种基于逆向重建和运动轨迹偏移的视频重定向质量客观评价算法。该算法通过减小目标函数平滑项的权重和删除黑边减少了错误匹配的情况,并提出网格损失率(Grid Loss Ratio,GLR)衡量未匹配区域的空间失真,且使用网格运动轨迹偏移量减少对SIFT-flow稠密匹配的依赖。与Multimedia Lab(ML)主观数据库的肯德尔相关系数达到0.593,其标准差为0.295。与其他算法相比,该算法能更好地评估重定向过程的失真,更符合人们的主观评价结果。

线上视频反馈早期干预对单调性扭动运动质量临床疗效的影响

目的探索线上视频反馈全身运动质量评估(GMA)超早期预测高危儿为单调性扭动运动者,实施医—家联合早期干预,观察其临床效果。方法收集高危儿门诊诊治的矫正胎龄45周前、经微信线上视频反馈GMA为单调性扭动运动的127例高危儿,其中男性61例,女性66例,失访5例;采用抛硬币法将其随机分为观察组(62例)和对照组(60例)。对照组患儿实施高危儿常规保健管理,观察组患儿在常规保健管理基础上给予微信线上视频反馈医—家联合早期干预,分别在纠正胎龄3月龄、10月龄进行Alberta婴儿运动量表评估、12月龄0~6岁儿心评估量表评估,比较2组患儿干预效果。结果2组患儿纠正胎龄3月龄Alberta婴儿运动量表评定AIMS分值比较差异无统计学意义(P>0.05);纠正胎龄10月龄时观察组Alberta婴儿运动量表评定AIMS总分高于对照组,差异有统计学意义(P<0.05),百分位数比较差异也有统计学意义(P<0.05)。12月龄0~6岁儿心评定量表评定适应能力、社交行为评分结果观察组分别高于对照组,差异有统计学意义(P<0.05)。结论通过微信线上视频反馈,及时给予患儿医—家联合早期干预,可以对高危儿GMA结果异常者有效改善患儿运动、适应及社交行为能力,适宜在高危儿管理中推广。

一种基于深度报文检测的合成视频质量评估方法

移动视频业务快速发展,用户感知与网络KPI指标发生偏离,传统视频运维支撑手段存在端到端问题定界难的问题。本文对国内电信运营商移动视频业务特性进行分析,提出一种基于深度报文检测的视频合成算法,将事务级的DPI单据进行关联,以一个完整的视频业务为单位输出相关体验评估信息,进而研究以业务级为基础的DPI指标,用于评估用户观看完整视频的全过程感知,提升用户感知保障。此方法能够覆盖主流的视频网站资源,本文所提出的方法经过实际应用验证,可真实评估视频质量及用户感知体验,助力实现国内电信运营商通信网络问题定界与网络自动驾驶。

基于时域复杂度的视频质量评估

在提高视频压缩编码效率的同时,要保证视频观看者的主观体验不下降.因此,研究视频质量评估算法有重要意义.视频的质量与视频帧的质量密切相关,通过主观质量评估实验研究视频序列质量与帧质量的关系,重点关注时域复杂度对视频质量的影响,得到了基于时域复杂度的视频序列质量与帧质量的关系模型.经验证,基于时域复杂度的视频质量评估模型计算得到的客观质量与主观质量有良好的一致性,性能表现优越,能够为视频编码算法的进一步优化提供依据.

矿山企业变配电站智能配电系统的分析研究

随着人工智能技术的不断深化,矿山企业配电系统也在发生深刻的变革,目前智能配电系统技术已成熟。基于配电系统的特点与需求,对传统配电系统提出了智能化的设计方案,用基于物联网或远程通讯功能的电气元件代替传统元件,对配电系统的设备以及环境进行实时监测,构建智能化系统架构。解决传统配电系统的运行维护中存在的人身安全以及维护困难问题,该系统对配电系统运行状态,对局部放电、电能质量,以及变配电站环境变量等进行实时监测,存入数据库中心,形成数据资产,对数据资产进行分析、处理,通过影响因素和语义分析库得出优化管理的建议和结论,实现配电系统智能化管理。

地面数字电视单频点同播4套高清节目的实践及视频质量评估

本文提出了一种利用视频质量评估来优化地面数字电视单频点同播高清节目套数的方法。根据我国地面数字电视(DTMB)信道编码、城市无线覆盖的实际情况,以及编码复用前后的视频序列,进行客观视频质量评估计算结果,优化播出设备参数,实现在保证终端接收视频质量的前提下,尽量提高数字电视无线传输覆盖的频带资源的利用效率。

结合视差补偿与3D数据处理的盲光场图像质量评价

与传统的2D图像相比,光场图像记录了场景中光线的强度和方向信息,在多媒体技术应用领域中占据着重要的地位。但在光场图像的产生、传输等处理过程中会不可避免地引入失真,影响用户视觉体验,因而需构建有效、准确的光场图像质量评价方法对其进行评估。本文基于光场图像的伪视频和极平面图像提出了结合视差补偿与3D数据处理的盲光场图像质量评价方法。首先,采用视差补偿模块处理光场图像伪视频序列,然后对经过视差补偿后的伪视频序列进行三维离散小波变换以及三维去均值对比度归一化处理,并提取频域和空域特征。同时,在极平面图像上提取方向梯度直方图特征表征其角度信息的失真。最后,运用支持向量机建立图像质量评价指标到主观质量得分的回归模型。所提算法在公开数据库NBU-LF1.0,Win5-LID和SHU上的PLCC分别达到0.886 1,0.928 7和0.976 9,实验结果表明,与经典的二维图像质量评价方法以及先进的光场图像质量评价方法相比,本文方法与主观质量评价结果的一致性更高。