A Multimodal Critical Discourse Analysis of Lingnan Cultural Promotional Videos on Social Media

In recent years,more and more directors of culture and tourism have taken part in the promotion of local cultural tourism by cross-dressing,talent shows,and pushing their limits on self-media platforms.This study investigates short videos of Lingnan culture promoted by directors general and deputy directors general of the Culture,Radio,Television,Tourism,and Sports Bureau of counties and cities in Guangdong Province on social media by the method of multimodal critical discourse analysis.The analysis of 33 videos shows that Lingnan culture is a domineering and confident culture,historical culture,graceful and elegant culture,and vibrant and active culture.Domineering and confident culture is embedded in the utterances and behaviors of the directors general or deputy directors general in the video.Historical culture is realized through the conversation with historical figures through time travel.Graceful and elegant culture is constructed in the depiction of sceneries and the depiction of characters’manners.Vibrant and active culture is represented in the depiction of the characters’actional process and analytical process.

Optimization and Performance Analysis of Intelligent Video AI Dynamic

In today’s information age,video data,as an important carrier of information,is growing explosively in terms of production volume.The quick and accurate extraction of useful information from massive video data has become a focus of research in the field of computer vision.AI dynamic recognition technology has become one of the key technologies to address this issue due to its powerful data processing capabilities and intelligent recognition functions.Based on this,this paper first elaborates on the development of intelligent video AI dynamic recognition technology,then proposes several optimization strategies for intelligent video AI dynamic recognition technology,and finally analyzes the performance of intelligent video AI dynamic recognition technology for reference.

Content-Based Hierarchical Analysis of News Video Using Audio and Visual Information

A schema for content-based analysis of broadcast news video is presented. First, we separate commercials from news using audiovisual features. Then, we automatically organize news programs into a content hierarchy at various levels of abstraction via effective integration of video, audio, and text data available from the news programs. Based on these news video structure and content analysis technologies, a TV news video Library is generated, from which users can retrieve definite news story according to their demands.

Customized Convolutional Neural Network for Accurate Detection of Deep Fake Images in Video Collections

The motivation for this study is that the quality of deep fakes is constantly improving,which leads to the need to develop new methods for their detection.The proposed Customized Convolutional Neural Network method involves extracting structured data from video frames using facial landmark detection,which is then used as input to the CNN.The customized Convolutional Neural Network method is the date augmented-based CNN model to generate‘fake data’or‘fake images’.This study was carried out using Python and its libraries.We used 242 films from the dataset gathered by the Deep Fake Detection Challenge,of which 199 were made up and the remaining 53 were real.Ten seconds were allotted for each video.There were 318 videos used in all,199 of which were fake and 119 of which were real.Our proposedmethod achieved a testing accuracy of 91.47%,loss of 0.342,and AUC score of 0.92,outperforming two alternative approaches,CNN and MLP-CNN.Furthermore,our method succeeded in greater accuracy than contemporary models such as XceptionNet,Meso-4,EfficientNet-BO,MesoInception-4,VGG-16,and DST-Net.The novelty of this investigation is the development of a new Convolutional Neural Network(CNN)learning model that can accurately detect deep fake face photos.

Collecting Traffic Video Data Using Portable Poles: Survey, Proposal, and Analysis

Several initiatives have been launched to help prevention of traffic accidents and near-accidents across the European Union. To aid the overall goal of reducing deaths and injuries related to traffic, one must understand the causation of the traffic accidents in order to prevent them. Rather than deploying a person to physically monitor a location, the task is eased by camera equipment installed in existing infrastructure, e.g. poles, and buildings, etc. In rural areas there is however a very limited infrastructure available which complicates the data acquisition. But even if there is infrastructure available in either the rural area or the urban area, this might not serve as an ideal position to capture video data from. In this work, we survey and provide an overview of available and relevant portable poles setups with respect to capturing data in both urban areas and rural areas. The conclusion of the survey shows a lack of a mobile, lightweight, compact, and easy deployable portable pole. We therefore design and develop a new portable pole meeting these requirements. The new proposed portable pole can be deployed by 2 persons in 2 hours in both rural areas as well as urban areas due to its compactness. The deployment and usage of the new portable pole is a complimentary tool, which may improve the camera capturing angle in case existing infrastructure is insufficient. This ultimately improves the traffic monitoring opportunities. Further, the survey of selected portable poles provides an excellent overview and can aid multiple applications within road traffic.

Analysis of video head impulse test saccades data in patients with vestibular migraine or probable vestibular migraine

Objective:Saccades accompanied by normal gain in video head impulse tests(vHIT)are often observed in patients with vestibular migraine(VM).However,they are not considered as an independent indicator,reducing their utility in diagnosing VM.To better understand clinical features of VM,it is necessary to understand raw saccades data.Methods:Fourteen patients with confirmed VM,45 patients with probable VM(p-VM)and 14 agematched healthy volunteers were included in this study.Clinical findings related to spontaneous nystagmus(SN),positional nystagmus(PN),head-shaking nystagmus(HSN),caloric test and vHIT were recorded.Raw saccades data were exported and numbered by their sequences,and their features analyzed.Results:VM patients showed no SN,PN or HSN,and less than half of them showed unilateral weakness(UW)on caloric test.The first saccades from lateral semicircular canal stimulation were the most predominant for both left and right sides.Neither velocity nor time parameters were significantly different when compared between the two sides.Most VM patients(86%)exhibited small saccades,around 35%of the head peak velocity,with a latency of 200e400 ms.Characteristics of saccades were similar in patients with p-VM.Only four normal subjects showed saccades,all unilateral and seemingly random.Conclusions:Small saccades involving bilateral semicircular canals with a scattered distribution pattern are common in patients with VM and p-VM.

AN HMM BASED ANALYSIS FRAMEWORK FOR SEMANTIC VIDEO EVENTS

Semantic video analysis plays an important role in the field of machine intelligence and pattern recognition. In this paper, based on the Hidden Markov Model (HMM), a semantic recognition framework on compressed videos is proposed to analyze the video events according to six low-level features. After the detailed analysis of video events, the pattern of global motion and five features in foreground—the principal parts of videos, are employed as the observations of the Hidden Markov Model to classify events in videos. The applications of the proposed framework in some video event detections demonstrate the promising success of the proposed framework on semantic video analysis.

Cloud‐based video streaming services:Trends,challenges,and opportunities

Cloud computing has drastically changed the delivery and consumption of live streaming content.The designs,challenges,and possible uses of cloud computing for live streaming are studied.A comprehensive overview of the technical and business issues surrounding cloudbased live streaming is provided,including the benefits of cloud computing,the various live streaming architectures,and the challenges that live streaming service providers face in delivering high‐quality,real‐time services.The different techniques used to improve the performance of video streaming,such as adaptive bit‐rate streaming,multicast distribution,and edge computing are discussed and the necessity of low‐latency and high‐quality video transmission in cloud‐based live streaming is underlined.Issues such as improving user experience and live streaming service performance using cutting‐edge technology,like artificial intelligence and machine learning are discussed.In addition,the legal and regulatory implications of cloud‐based live streaming,including issues with network neutrality,data privacy,and content moderation are addressed.The future of cloud computing for live streaming is examined in the section that follows,and it looks at the most likely new developments in terms of trends and technology.For technology vendors,live streaming service providers,and regulators,the findings have major policy‐relevant implications.Suggestions on how stakeholders should address these concerns and take advantage of the potential presented by this rapidly evolving sector,as well as insights into the key challenges and opportunities associated with cloud‐based live streaming are provided.

Background modeling methods in video analysis： A review and comparative evaluation

Foreground detection methods can be applied to efficiently distinguish foreground objects including moving or static objects from back- ground which is very important in the application of video analysis, especially video surveillance. An excellent background model can obtain a good foreground detection results. A lot of background modeling methods had been proposed, but few comprehensive evaluations of them are available. These methods suffer from various challenges such as illumination changes and dynamic background. This paper first analyzed advantages and disadvantages of various background modeling methods in video analysis applications and then compared their performance in terms of quality and the computational cost. The Change detection.Net （CDnet2014） dataset and another video dataset with different envi- ronmental conditions （indoor, outdoor, snow） were used to test each method. The experimental results sufficiently demonstrated the strengths and drawbacks of traditional and recently proposed state-of-the-art background modeling methods. This work is helpful for both researchers and engineering practitioners. Codes of background modeling methods evaluated in this paper are available atwww.yongxu.org/lunwen.html.

Critical Discourse Analysis of City Cultural Identity Construction—A Case Study of Video Xi tang

With the rapid development of science and technology,video has become a very important way to demonstrate the city itself.This paper,based on Fairclough's three-dimensional conception of discourse to the video of Xitang,analyzes the on-screen titles of this video to reveal the ideology behind it.Through the analysis,it points out that this video,while protecting Xitang's own unique traditional characteristics,it tries to cater for the needs not only Chinese people but also foreigners.To some extent,it tries to promote Xitang itself.

Shearlet Based Video Fingerprint for Content-Based Copy Detection

Content-based copy detection (CBCD) is widely used in copyright control for protecting unauthorized use of digital video and its key issue is to extract robust fingerprint against different attacked versions of the same video. In this paper, the “natural parts” (coarse scales) of the Shearlet coefficients are used to generate robust video fingerprints for content-based video copy detection applications. The proposed Shearlet-based video fingerprint (SBVF) is constructed by the Shearlet coefficients in Scale 1 (lowest coarse scale) for revealing the spatial features and Scale 2 (second lowest coarse scale) for revealing the directional features. To achieve spatiotemporal natural, the proposed SBVF is applied to Temporal Informative Representative Image (TIRI) of the video sequences for final fingerprints generation. A TIRI-SBVF based CBCD system is constructed with use of Invert Index File (IIF) hash searching approach for performance evaluation and comparison using TRECVID 2010 dataset. Common attacks are imposed in the queries such as luminance attacks (luminance change, salt and pepper noise, Gaussian noise, text insertion);geometry attacks (letter box and rotation);and temporal attacks (dropping frame, time shifting). The experimental results demonstrate that the proposed TIRI-SBVF fingerprinting algorithm is robust on CBCD applications on most of the attacks. It can achieve an average F1 score of about 0.99, less than 0.01% of false positive rate (FPR) and 97% accuracy of localization.

Nonlinear Dynamic Analysis of MPEG-4 Video Traffic

The main research motive is to analysis and to veiny the inherent nonlinear character of MPEG-4 video. The power spectral density estimation of the video trafiic describes its 1/f^β and periodic characteristics.The priraeipal compohems analysis of the reconstructed space dimension shows only several principal components can be the representation of all dimensions. The correlation dimension analysis proves its fractal characteristic. To accurately compute the largest Lyapunov exponent, the video traffic is divided into many parts.So the largest Lyapunov exponent spectrum is separately calculated using the small data sets method. The largest Lyapunov exponent spectrum shows there exists abundant nonlinear chaos in MPEG-4 video traffic. The conclusion can be made that MPEG-4 video traffic have complex nonlinear be havior and can be characterized by its power spectral density,principal components, correlation dimension and the largest Lyapunov exponent besides its common statistics.

Video Analysis Based on Volumetric Event Detection

During the past decade, feature extraction and knowledge acquisition based on video analysis have been extensively researched and tested on many applications such as closed-circuit television （CCTV） data analysis, large-scale public event control, and other daily security monitoring and surveillance operations with various degrees of success. However, since the actual video process is a multi-phased one and encompasses extensive theories and techniques ranging from fundamental image processing, computational geometry and graphics, and machine vision, to advanced artificial intelligence, pattern analysis, and even cognitive science, there are still many important problems to resolve before it can be widely applied. Among them, video event identification and detection are two prominent ones. Comparing with the most popular frame-to-frame processing mode of most of today＇s approaches and systems, this project reorganizes video data as a 3D volume structure that provides the hybrid spatial and temporal information in a unified space. This paper reports an innovative technique to transform original video frames to 3D volume structures denoted by spatial and temporal features. It then highlights the volume array structure in a so-called ＂pre-suspicion＂ mechanism for a later process. The focus of this report is the development of an effective and efficient voxel-based segmentation technique suitable to the volumetric nature of video events and ready for deployment in 3D clustering operations. The paper is concluded with a performance evaluation of the devised technique and discussion on the future work for accelerating the pre-processing of the original video data.

Methodology for Detecting Strabismus through Video Analysis and Intelligent Mining Techniques

:Strabismus is a medical condition that is defined as the lack of coordination between the eyes.When Strabismus is detected at an early age,the chances of curing it are higher.The methods used to detect strabismus and measure its degree of deviation are complex and time-consuming,and they always require the presence of a physician.In this paper,we present a method of detecting strabismus and measuring its degree of deviation using videos of the patient’s eye region under a cover test.Our method involves extracting features from a set of training videos(training corpora)and using them to build a classifier.A decision tree(ID3)is built using labeled cases from actual strabismus diagnosis.Patterns are extracted from the corresponding videos of patients,and an association between the extracted features and actual diagnoses is established.Matching Rules from the correlation plot are used to predict diagnoses for future patients.The classifier was tested using a set of testing videos(testing corpora).The results showed 95.9%accuracy,4.1%were light cases and could not be detected correctly from the videos,half of them were false positive and the other half was false negative.

Open-Access Framework for Efficient Object-Oriented Development of Video Analysis Software

The increasing use of digital video everyday in a multitude of electronic devices, including mobile phones, tablets and laptops, poses the need for quick development of cross-platform video software. However current approaches to this direction usually require a long learning curve, and their development lacks standardization. This results in software components that are difficult to reuse, and hard to maintain or extend. In order to overcome such issues, we propose a novel object-oriented framework for efficient development of software systems for video analysis. It consists of a set of four abstract components, suitable for the implementation of independent plug-in modules for video acquisition, preprocessing, analysis and output handling. The extensibility of each module can be facilitated by sub-modules specifying additional functionalities. This architecture enables quick responses to changes and re-configurability;thus conforming to the requirements of agile software development practices. Considering the need for platform independency, the proposed Java Video Analysis (JVA) framework is implemented in Java. It is publicly available through the web as open-access software, supported by a growing collection of implemented modules. Its efficiency is empirically validated for the development of a representative video analysis system.

Video Analysis of Side Hop Technique in Trials

Trials is a specialty of off-road cycling in which the rider has to face obstacle courses without resting feet on the ground. Technique in this sport has a great importance, since it reduces the risk of committing penalties and allows more efficient execution of the gesture. To improve technique, the motion analysis allows to study the gesture both qualitatively and quantitatively. In this work video analysis was used to study the side hop from rear wheel technique. Two different executions of this technique were analyzed. The primary purpose is the identification of the phases that make up the technical gesture. It was given an explanation to the movement strategies adopted in the execution of the jump in the two different situations.

Analysis of the Public Visual Consumption Turn behind the Popularity of Short Video

From WeChat,QQ to Weibo,Tik Tok this series of online social networking applications,especially with the increasingly maturity of online shopping in recent years,short video and mobile intelligence have been developing rapidly,which have strongly influenced many people’s living habits and shopping habits.Their development not only promotes the social and economic development,but also produces a new form of visual communication.This paper discusses the characteristics of short video,analyzes the shift of public visual consumption behind the popularity of short video,and hopes to further build a healthy development path of short video.

Mass asymmetry and tricyclic wobble motion assessment using automated launch video analysis

This paper describes an approach to identify epicyclic and tricyclic motion during projectile flight caused by mass asymmetries in spinstabilized projectiles. Flight video was captured following projectile launch of several M110A2E1 155 mm artillery projectiles. These videos were then analyzed using the automated flight video analysis method to attain their initial position and orientation histories.Examination of the pitch and yaw histories clearly indicates that in addition to epicyclic motion's nutation and precession oscillations, an even faster wobble amplitude is present during each spin revolution, even though some of the amplitudes of the oscillation are smaller than 0.02 degree.The results are compared to a sequence of shots where little appreciable mass asymmetries were present, and only nutation and precession frequencies are predominantly apparent in the motion history results. Magnitudes of the wobble motion are estimated and compared to product of inertia measurements of the asymmetric projectiles.

视频数据库管理软件Tac Analysis在竞技体育中的应用

以全面实现榆林市竞技体育信息化管理为根本目的,设计出了视频数据库管理软件Tac Analysis。该系统采用C语言编程,基于SQL(Microsoft SQL Server)数据库技术进行数据库软件开发,实现了视频分割、标记、检索以及合并等功能。在运行过程中视频数据库管理软件Tac Analysis在操作性上具有明显优势,使用者可以随时、快速地查找视频资料,有效地提升了榆林市竞技体育信息化管理的水平。

基于Vernier Video Physics软件的物理实验探究——以“探究平抛运动的特点”为例

智能手机的飞速发展和智能手机APP的不断更新对当今社会的各个方面都产生了深远的影响。与此同时,智能手机APP也逐渐被引入课堂教学中,为学生提供了自主学习的机会,也使物理实验教学模式发生了巨大的改变,成了广大教育者关注的热点。利用Vernier Video Physics软件和Vernier Graphical Analysis软件,再结合平抛运动实验仪,对小钢球的运动轨迹进行逐帧追踪定位,得到小钢球做平抛运动的y-x图像、x-t图像、y-t图像和v_(y)-t图像,再对图像进行相应函数拟合,经过数据分析,得到小钢球做平抛运动在水平方向和竖直方向的运动特点。利用智能手机APP辅助高中物理实验教学可以激发学生的学习兴趣,帮助学生理解物理概念和规律,使学生积极主动地参与到实验中来,培养他们的动手能力,提升他们的实验素养。