Human-computer Interaction Technology Research Articles

Research on Visual Thinking of Computer UI Design Based on User Interaction Experience

UI design (hereinafter referred to as UID) is an interface design concept that attaches importance to User Interaction Experience (hereinafter referred to as UIE), which is a way to improve user experience through visual communication technology. Therefore, UID has unique personality and taste, which will bring the audience corresponding visual senses, such as shock, impact, comfort, freedom, etc. Through UID, we can build habits that are more in line with user cognition, which can help the audience recognize user design more. With the popularity of computer technology, human-computer interaction technology has gradually diversified, which requires us to study the UI technology. We must cultivate Visual Thinking (hereinafter referred to as VT), which will better complete the interactive experience. Firstly, this paper analyzes the related concepts. Then, this paper analyzes the guidance of VT cognitive process to art design. Finally, some suggestions are put forward.

Research on the Application of Multimedia Technology in French Listening Teaching

With the increasingly frequent exchanges between China and France, the demand for French talents in China is increasing. Therefore, our country must improve the quality of French teaching, which will better meet the needs of society. With the popularity of the Internet, Multimedia Technology (hereinafter referred to as MT) has been applied to teaching, such as French listening, which will better assist listening. MT has many characteristics, including strong comprehensiveness and wide application, which will be introduced into French teaching. Through practice, we can reflect in the good teaching effect, which will be applied to the teaching of French advanced listening. Through MT, we can establish a new technology of logical relationship and human-computer interaction, which will integrate multiple functions. Therefore, we must apply MT to French Listening Teaching (hereinafter referred to as LT), which will enhance and stimulate learning interest. Through MT, we can enrich the French LT resources, which will improve the teaching efficiency. Firstly, this paper analyzes the importance of multimedia assisted LT. Then, this paper puts forward some problems. Finally, some suggestions are put forward.

The Motor Function Evaluation of College Students' Physical Activity State From the Perspective of Educational Psychology.

College students have taken part in less and less physical activities as a result of the common static lifestyle in recent years, lowering the level of motor function. This phenomenon has been a source of concern for schools and the government, and it is necessary to take corresponding measures to change it. The general motor function level of Chinese college students is explored first based on artificial intelligence and the human–computer interaction technology. The Physical Activity Questionnaire for College Students is compiled by referring to the International Physical Activity Questionnaire, and 561 students from colleges in Tianjin province are assessed based on the functional movement screen (FMS). Spearman correlation and multivariate regression analysis (MRA) are used to analyze the correlation between the motor function and physical activity status. In terms of lunch break frequency, the proportion of students having one to two lunch breaks in a week is the highest (54.15%); in terms of the frequency of doing moderate physical exercise, the proportion of students doing moderate physical exercise for 1–2 days in a week is the highest (50.61%); in terms of the frequency of doing heavy physical exercise, the proportion of students doing heavy exercise for 1–2 days in a week is the highest (47.26%); in terms of the sedentary time, the proportion of students with sedentary time more than 5 h in a day is the highest (40.61%); in terms of eye use time, the proportion of students with 8–10 h eye use time in a day is the highest (43.61%). Besides, in terms of the FMS score, the proportion of students with 13–15 FMS is the highest (48.46%). The hurdle step (21.03%), straight knee lift (22.52%), and body rotation stability (18.31%) have a relatively low proportion among the three-point items. There is a positive correlation between motor function score with the time of moderate exercise and the time of heavy exercise (P < 0.05). College students generally have insufficient rest time, long eye use time, and long sitting time, leading to a low level of motor function, manifested by an asymmetry between both sides of the body and poor trunk stability. It is recommended to add hurdling steps, straight knee lifts, and body rotation stability tests to college physical education courses.

Gesture Recognition Method Based on Attention Mechanism for Complex Background

Human-computer interaction technology is still an unaccomplished goal due to complex background and changeable lighting conditions. A two-stage gesture recognition method is proposed to improve the accuracy of gesture recognition. The first stage combines attention mechanism and atrous spatial pyramid pooling (ASPP) which aims to segment gesture from complex background. The second stage uses a two stream convolutional neural network, combines features from the original picture and the output of the first stage, aims to realize the classification of gestures. It can recognize gestures more accurately compared with other gesture recognition methods.

The Use of Deep Learning and VR Technology in Film and Television Production From the Perspective of Audience Psychology.

As the development of artificial intelligence (AI) technology, the deep-learning (DL)-based Virtual Reality (VR) technology, and DL technology are applied in human-computer interaction (HCI), and their impacts on modern film and TV works production and audience psychology are analyzed. In film and TV production, audiences have a higher demand for the verisimilitude and immersion of the works, especially in film production. Based on this, a 2D image recognition system for human body motions and a 3D recognition system for human body motions based on the convolutional neural network (CNN) algorithm of DL are proposed, and an analysis framework is established. The proposed systems are simulated on practical and professional datasets, respectively. The results show that the algorithm's computing performance in 2D image recognition is 7–9 times higher than that of the Open Pose method. It runs at 44.3 ms in 3D motion recognition, significantly lower than the Open Pose method's 794.5 and 138.7 ms. Although the detection accuracy has dropped by 2.4%, it is more efficient and convenient without limitations of scenarios in practical applications. The AI-based VR and DL enriches and expands the role and application of computer graphics in film and TV production using HCI technology theoretically and practically.

Research on Human Motion Monitoring Method Based on Multi-Joint Constraint Filter Model

In recent years, with the increasing application of human motion monitoring technology in virtual reality, medical health, human-computer interaction, and other fields, higher requirements have been put forward for measurement accuracy. Aiming at the problem of large accumulative measurement error and multi-joint constraint in the traditional inertial measurement system, a multi-joint constrained filter model human motion monitoring method based on data fusion is proposed. Firstly, an accelerometer and magnetometer are used to construct the initial attitude angle calculation model of the human body at rest. Secondly, combined with gyroscope, accelerometer and magnetometer, the attitude optimal estimation model based on Extended Kalman Filter (EKF) algorithm for human body motion was established. Then, a global coordinate system of human multi-joints is established, and the joint constraint is introduced into the attitude optimal estimation model by using the estimation projection method, and the multi-joint constraint filtering model of human motion monitoring is constructed. Finally, a multi-inertial measurement unit (MIMU) human motion monitoring system was built, and the simulation and experimental analysis were carried out. The experimental results show that the maximum angular measurement error is about 1° after filtering with the motion monitoring method proposed in this paper. Compared with the existing algorithm, the accuracy of the three angle measurements is improved by 38.2%, 39.3% and 67.4%, respectively. Based on this, the human motion monitoring system designed can effectively monitor human motion.

Design of Intelligent Firefighter Helmet Based on AR Technology

Traditional firefighter helmet has the disadvantages of poor shading and lack of flexibility. AR is the process of computing 3d coordinate points according to the image points of real objects, and then superimposing “virtual + real” surreal scenes based on real scenery through the calculation simulation of the processor. The AR firefighter helmet is a new type of firefighting protective that uses AR technology in traditional firefighter helmet. Intelligent firefighter helmet based on AR technology uses 3D simulation imaging technology, thermal camera tracking technology, human-computer interaction technology, and code recognition technology to maximize the effect of realistic fire scenes. It can enable firefighters to see the real situation in the scene of heavy smoke and improve the efficiency of rescue. Therefore, firefighter helmets with AR equipment represent the future development trend of firefighter helmet. This paper discusses the theory, value, technical operation, design and development of intelligence. The research on the fireman’s helmet based on augmented reality technology has leading advantages and application value.

Research on Semantic Feature Disambiguation Based on Improved Collaborative Filtering Algorithm

Artificial intelligence is developing rapidly, and the amount of information data is also increasing. Human-computer interaction technology can use computers to understand and process massive amounts of large data texts and accurately locate useful information. Moreover, it is very difficult to achieve smooth human-computer interaction. The main reason for the difficulty is that there are various ambiguities in natural language. Therefore, a noun phrase referential disambiguation model is established by improving the convolutional collaborative filtering algorithm in the paper, where the hand-crafted features are applied to clean up data to remove redundancy, and the remaining correct data is used as the input of the model. After experiments, the MACSSR algorithm and the CSSR algorithm are used for comparative testing under different M directs. It proves that the research content of this paper is superior to the comparative test method, and can extract semantic dependencies more quickly and effectively, which contributes to the intelligent semantic disambiguation technology.

Reviewing a Decade of Human-Computer Interaction for Development (HCI4D) Research, as One of Best's "Grand Challenges"

The human-computer interaction for development (HCI4D) field emerged at the intersection of the fields of information and communication technology for development (ICT4D) and human-computer interaction (HCI). In 2010, Michael Best nominated HCI4D as one of ICT4D's "grand challenges". This HCI4D field is now entering its second decade, and it is important to reflect on the research that has been conducted, and to consider how HCI4D researchers have addressed the challenge that constitutes the raison d'etre of HCI4D's existence. Best provided four guidelines to inform researchers embracing this challenge. This study commences by identifying the primary HCI4D-specific themes, and then carries out a systematic literature review of the HCI4D literature to build a corpus to support the analysis. The corpus is analysed to reflect on how well the field's practices align with Best's guidelines. The overall finding is that HCI4D researchers have largely been following Best's guidelines and that the HCI4D field is demonstrating encouraging signs of emerging maturity.

Research on Digital Cultural Creation Design of The Palace Museum from the Perspective of Symbol consumption -- A Case study of Twelve Beauties of Prince Yong

With the development of digital technology, mobile terminals have become a new medium for museum cultural and creative products to spread the connotation of art and culture. The innovation of digital technology has caused corresponding changes in the design of cultural and creative products, and various digital cultural and creative products have been created on its basis. The emergence of digital technologies such as mobile Internet, cloud computing, AI, VR, human-computer interaction, and 5G communication technology has brought broader development prospects for digital creative design. This article studies the concepts of cultural symbols and design methods of the digital cultural and creative products of The Palace Museum to provide new ideas for the design of digital cultural and creative products of the museum. We choose Twelve Beauties of Prince Yong as an example, the first digital cultural creation product of The Palace Museum.

Role of Human Body Posture Recognition Method Based on Wireless Network Kinect in Line Dance Aerobics and Gymnastics Training

With the rapid development of the information society, human body gesture recognition has become an important technology for human‐computer interaction. This paper combines Kinect’s human bone monitoring technology with auxiliary gymnastics training. The gymnastics and dance training can correct students’ wrong movements in time through feedback and improve the training efficiency, so as to meet the needs of nature and harmony of human‐machine interaction. In this paper, based on the wireless network Kinect, the human body posture recognition method and tracking technology are studied, and the joint point angle representation method based on the fixed axis is proposed, and the posture recognition method based on the joint point angle is improved, which can accurately recognize the human body posture. Aiming at the situation that the human joint points are occluded, the human joint point repair algorithm is improved. The algorithm is based on the proportion of human bone nodes and the characteristics of human motion, and based on geometric principles, it repairs the occluded points. The feasibility of the original joint point data, angle feature, and distance feature in expressing human behavior is analyzed through experiments, a standard gymnastics movement database is established, and new gymnastics movements can be entered at any time. A gymnastics auxiliary training system is designed, which can analyze and evaluate the exercises of the trainer from the joint point coordinates and the angle formed by the joints and provide the trainer with intuitive error correction prompts. The human body posture recognition method studied in this paper can accurately give the difference between the trainer’s movement and the standard movement, and the trainer can adjust the movement posture according to the prompts, improve the level of gymnastics, and achieve the purpose of auxiliary training. Experiments show that the algorithm model has an accuracy rate of 95.7% for human body posture recognition, and it plays a huge role in line dance aerobics and gymnastics training.

The Improved ELM Algorithms Optimized by Bionic WOA for EEG Classification of Brain Computer Interface

The breakthrough of electroencephalogram (EEG) signal classification of brain computer interface (BCI) will set off another technological revolution of human computer interaction technology. Because the collected EEG is a type of nonstationary signal with strong randomness, effective feature extraction and data mining techniques are urgently required for EEG classification of BCI. In this paper, the new bionic whale optimization algorithms (WOA) are proposed to promote the improved extreme learning machine (ELM) algorithms for EEG classification of BCI. Two improved WOA-ELM algorithms are designed to compensate for the deficiency of random weight initialization for basic ELM. Firstly, the top several best individuals are selected and voted to make decisions to avoid misjudgment on the best individual. Secondly, the initial connection weights and bias between the input layer nodes and hidden layer nodes are optimized by WOA through bubble-net attacking strategy (BNAS) and shrinking encircling mechanism (SEM), and different regularization mechanisms are introduced in different layers to generate appropriate sparse weight matrix to promote the generalization performance of the algorithm.As shown in the contrast results, the average accuracy of the proposed method can reach 93.67%, which is better than other methods on BCI dataset.

Research on the Teaching Model of Animation Professional Class Based on AR/VR Technology and 5G Network

The use of emerging technologies is becoming more common in today’s world, and as media integration deepens, so does the use of virtual reality technology. As an emerging science and technology, VR/AR technology plays a critical role in society’s development and progress, and its application in current education and teaching has become an indispensable link. The production of high‐quality animation professionals is the society’s and the animation industry’s urgent need for talent, the precondition for the prosperity of cultural and creative industries, and the foundation of national soft power. To bring more technical changes to education and provide theoretical support for the realization of human‐computer interaction technology, this paper mainly elaborates on the concept and application fields of VR/AR technology and discusses the specific applications of VR/AR technology according to its different educational stages. The main point of the presentation is to demonstrate how, in the era of 5G networks, large bandwidth, ultralow latency, massive connectivity, and ultrahigh reliability provide a strong network foundation for widespread VR/AR application. We will investigate the paucity of teaching methods, teaching modes, and teaching platforms as a result of the application of 5G‐based VR/AR technology in the teaching field of animation majors, as well as the design of teaching methods, teaching modes, and experimental training platforms based on 5G‐based VR/AR technology in animation majors in conjunction with the training plan of engineering students at our university. We will delve deeper into the integration of VR/AR technology and higher education teaching, laying the groundwork for “AI+” education. VR/AR technology can be used in the classroom to present information to students in a more three‐dimensional and intuitive way, which not only increases student interest in learning but also improves the learning experience and cultivates core literacy.

Gesture Recognition Based on Improved YOLOv4-tiny Algorithm

With the development of human-computer interaction, gesture recognition is becoming more and more important. At the same time, mobile applications are developing rapidly, it is a development trend to implement human-computer interaction technology on the mobile terminal. An improved YOLOv4-tiny gesture recognition algorithm is proposed. Firstly, on the basis of YOLOv4-tiny network, the Spatial Pyramid Pooling(SPP) module is added to integrate the local and global features of the image to enhance the accurate positioning ability of the network. Secondly, a 1×1 convolution is added after the 3 maximum pooling layers of the original YOLOv4-tiny network and the newly added SPP module, which reduces the network parameters and improves the prediction speed of the network. On this basis, the K-means++ algorithm is used to generate an anchor box suitable for detecting gestures to speed up the network detection of gestures. In the gesture dataset NUS-II, compared with the YOLOv3-tiny algorithm and the YOLOv4-tiny algorithm, the improved algorithm mean Average Precision(mAP) is 100%, Frames Per Second(FPS) is 377, which can detect and recognize gestures quickly and accurately. The improved algorithm of this paper is deployed on the Android mobile terminal to realize the real-time gesture detection and recognition on the mobile terminal, which has great research significance for the development of human-computer interaction.

Gesture Recognition Based on Multiscale Singular Value Entropy and Deep Belief Network

As an important research direction of human–computer interaction technology, gesture recognition is the key to realizing sign language translation. To improve the accuracy of gesture recognition, a new gesture recognition method based on four channel surface electromyography (sEMG) signals is proposed. First, the S-transform is applied to four channel sEMG signals to enhance the time-frequency detail characteristics of the signals. Then, multiscale singular value decomposition is applied to the multiple time-frequency matrix output of S-transform to obtain the time-frequency joint features with better robustness. The corresponding singular value permutation entropy is calculated as the eigenvalue to effectively reduce the dimension of multiple eigenvectors. The gesture features are used as input into the deep belief network for classification, and nine kinds of gestures are recognized with an average accuracy of 93.33%. Experimental results show that the multiscale singular value permutation entropy feature is especially suitable for the pattern classification of the deep belief network.

A New Gaze Estimation Method Based on Homography Transformation Derived from Geometric Relationship

In recent years, the gaze estimation system, as a new type of human-computer interaction technology, has received extensive attention. The gaze estimation model is one of the main research contents of the system. The quality of the model will directly affect the accuracy of the entire gaze estimation system. To achieve higher accuracy even with simple devices, this paper proposes an improved mapping equation model based on homography transformation. In the process of experiment, the model mainly uses the “Zhang Zhengyou calibration method” to obtain the internal and external parameters of the camera to correct the distortion of the camera, and uses the LM(Levenberg-Marquardt) algorithm to solve the unknown parameters contained in the mapping equation. After all the parameters of the equation are determined, the gaze point is calculated. Different comparative experiments are designed to verify the experimental accuracy and fitting effect of this mapping equation. The results show that the method can achieve high experimental accuracy, and the basic accuracy is kept within 0.6∘. The overall trend shows that the mapping method based on homography transformation has higher experimental accuracy, better fitting effect and stronger stability.

Cognitive Manufacturing in Industry 4.0 toward Cognitive Load Reduction: A Conceptual Framework

Cognitive manufacturing utilizes cognitive computing, the industrial Internet of things (IoT), and advanced analytics to upgrade manufacturing processes in manners that were not previously conceivable. It enables associations to improve major business measurements, for example, productivity, product reliability, quality, and safety, while decreasing downtime and lowering costs. Considering all the facts that can prejudice the manufacturing performance in Industry 4.0, the cognitive load has received more attention, since it was previously neglected with respect to manufacturing industries. This paper aims to investigate what causes cognitive load reduction in manufacturing environments, i.e., human–computer interaction technologies that reduce the identified causes and the applications of cognitive manufacturing that use the referred technologies. Thus, a conceptual framework that links cognitive manufacturing to a reduction of the cognitive load was developed.

RETRACTED ARTICLE: A smart position optimization scheme for badminton doubles based on human–computer interactive training in wireless sensor networks

In the continuous development process, robot technology based on multimedia interactions has been widely used in aerospace, medical, education and service industries. The relationship between robots and humans is getting closer. The improvement of robot intelligence is a process of continuously learning the outside world. Since 1959, multimedia human–computer interaction technology has provided more and more technical support for human research robots. In this paper, we firstly study the characteristics of badminton competition, including the technical characteristics, tactics characteristics, and the collection requirements about on-site training. The technical description of the badminton doubles station is also completed. Furthermore, in terms of the digitalization of the gait-based sensation, the automated acquisition of the gait technology, the simultaneously with the video, and the high-speed imaging system, the system implement information is integrated. After that, badminton multimedia techniques and tactics are designed based on the extensive statistical analysis. The skills and tactics of athletes are expressed in the form of video, graphics and text. Finally, the operators can carry out the technical and tactical analysis processes through good human–computer interactions. This increases the end user’s game information. The related attention and understanding can strengthen the strength and depth of technical and tactical ability analysis. Thus, we propose the station optimization plan for badminton doubles.

Preface

The rise of new technology for Industry 4.0, we aim to discover how Virtual and Mixed Reality Interfaces fit to Industry 4.0. International Conference on Virtual and Mixed Reality Interfaces 2020 (ICVRMR2020) brings an opportunity to invite new innovative inventions on Computer Graphics, Multimedia, Image Processing, Human Computer Interaction, Animation, Web and Mobile Technology, Games and Emerging Technology especially in Virtual and Augmented/Mixed Reality. Due to the COVID-19 pandemic situation all around the globe, we have organized this conference into virtual conference and the method is virtual presentation for all International and local participants. ICVRMR2020 is a strategic step to develop a research network in the field of Computer Graphics, Multimedia, Image Processing, Human Computer Interaction, Animation, Web and Mobile Technology, Games and Emerging Technology especially in Virtual and Augmented/Mixed Reality. UTM ViCubelab Research Group brings this virtual conference to provide the opportunities for academicians, professionals, practitioners and policy makers in the engineering and computing fields to share their thoughts and empirical works on Virtual Reality and Augmented/Mixed Reality inline with the rise of new industrial digital technology. Therefore, we still held this conference even though it is virtually through the Webex application. Outcome from this conference can be a benchmark for future research and development, and become a trigger point for developing research and development collaborations. It also serves to foster communication among researchers and practitioners working in a wide variety of scientific areas with a common interest in Engineering and Applied Computing.Thank you. Dr. Ajune Wanis Ismail Chair of ICVRMR 2020List of Organising Committee, Honorary Chair, Chair, Co-chair, Publication Chair, Our Committee are available in this pdf.

Application Research of Virtual Reality Technology

Virtual reality technology is an important subject in the 21st century, as well as one of the important technologies affecting people’s lives. The characteristic of the latest technology in the field of computer is to create a virtual environment for users in an imitative way, and to make users feel immersed in the virtual environment through perceptual behaviors such as seeing, hearing and touching, and interact with the virtual environment to cause real-time changes of the virtual environment. Virtual reality technology integrates computer graphics technology, multimedia technology, human-computer interaction technology, network technology, three-dimensional display technology and simulation technology, and it is the latest technology in the field of computer science and technology that has been developed comprehensively. It is also the comprehensive application of mechanics, mathematics, optics, mechanism kinematics and other disciplines. This paper fully discusses the research status of virtual reality technology at home and abroad, and forecasts the development trend of virtual reality.