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Computers, Materials & Continua 2024年第5期79卷 3047-3065页

作者： Chanho Park Takefumi Ogawa Graduate School of Engineering The University of TokyoTokyo113-0033Japan Information Technology Center The University of TokyoChiba277-0882Japan

Six degrees of freedom(6DoF)input interfaces are essential formanipulating virtual objects through translation or rotation in three-dimensional(3D)space.A traditional outside-in tracking controller requires the installation of expensive hardware in advance.While inside-out tracking controllers have been proposed,they often suffer from limitations such as interaction limited to the tracking range of the sensor(e.g.,a sensor on the head-mounted display(HMD))or the need for pose value modification to function as an input interface(e.g.,a sensor on the controller).This study investigates 6DoF pose estimation methods without restricting the tracking range,using a smartphone as a controller in Augmented reality(AR)environments.Our approach involves proposing methods for estimating the initial pose of the controller and correcting the pose using an inside-out tracking approach.In addition,seven pose estimation algorithms were presented as candidates depending on the tracking range of the device sensor,the tracking method(e.g.,marker recognition,visual-inertial odometry(VIO)),and whether modification of the initial pose is necessary.Through two experiments(discrete and continuous data),the performance of the algorithms was evaluated.The results demonstrate enhanced final pose accuracy achieved by correcting the initial pose.Furthermore,the importance of selecting the tracking algorithm based on the tracking range of the devices and the actual input value of the 3D interaction was emphasized.

关键词： Smartphone inside-out tracking 6DoF pose 3D interaction Augmented reality

Context-Aware Augmented reality Using Human-Computer Interaction Models

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Journal of Control and Decision 2024年第1期11卷 1-14页

作者： Ying Sun Qiongqiong Guo Shumei Zhao Karthik Chandran G.Fathima Henan intelligent education and intelligent technology application engineering technology research center Zhengzhou Railway Vocational and technical collegeZhengzhouHenanPeople’s Republic of China Henan Provincial Research Center of Wisdom Education and Intelligent Technology Application Engineering Technology Zhengzhou Railway Vocational and technical collegeZhengzhouHenanPeople’s Republic of China Department of Mechatronics Engineering Jyothi Engineering CollegeKeralaIndia CSE Adhiyamaan College of Engineering HosurTamilnaduIndia

Augmented reality is a technique that allows users to overlap digital information with their physical world.The Augmented reality(AR)displays have an exceptional characteristic from the Human–Computer Interaction(HCI)perspective.Due to its increasing popularity and application in diverse domains,increasing user-friendliness and AR usage are critical.Context-aware is one approach since an AR application can adapt to the user,environment,needs and enhance ergonomic principles and functionality.This paper proposes the Intelligent Contextaware Augmented reality Model(ICAARM)for Human–Computer Interaction systems.This study explores and reduces interaction uncertainty by semantically modeling user-specific interaction with context,allowing personalised interaction.Sensory information is captured from an AR device to understand user interactions and context.These depictions carry semantics to Augmented reality applications about the user’s intention to interact with a specific device affordance.Thus,this study describes personalised gesture interaction in VR/AR applications for immersive/intelligent environments.

关键词： Augmented reality Context-aware Human–Computer Interaction

Leveraging Augmented reality,Semantic-Segmentation,and VANETs for Enhanced Driver’s Safety Assistance

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Computers, Materials & Continua 2024年第1期78卷 1443-1460页

作者： Sitara Afzal Imran Ullah Khan Irfan Mehmood Jong Weon Lee Mixed reality and Interaction Lab Department of SoftwareSejong UniversitySeoul05006Korea Faculty of Engineering and Digital Technologies School of Computer ScienceAI and ElectronicsUniversity of BradfordBradfordUK

Overtaking is a crucial maneuver in road transportation that requires a clear view of the road ahead.However,limited visibility of ahead vehicles can often make it challenging for drivers to assess the safety of overtaking maneuvers,leading to accidents and fatalities.In this paper,we consider atrous convolution,a powerful tool for explicitly adjusting the field-of-view of a filter as well as controlling the resolution of feature responses generated by Deep Convolutional Neural Networks in the context of semantic image segmentation.This article explores the potential of seeing-through vehicles as a solution to enhance overtaking safety.See-through vehicles leverage advanced technologies such as cameras,sensors,and displays to provide drivers with a real-time view of the vehicle ahead,including the areas hidden from their direct line of sight.To address the problems of safe passing and occlusion by huge vehicles,we designed a see-through vehicle system in this study,we employed a windshield display in the back car together with cameras in both cars.The server within the back car was used to segment the car,and the segmented portion of the car displayed the video from the front car.Our see-through system improves the driver’s field of vision and helps him change lanes,cross a large car that is blocking their view,and safely overtake other vehicles.Our network was trained and tested on the Cityscape dataset using semantic segmentation.This transparent technique will instruct the driver on the concealed traffic situation that the front vehicle has obscured.For our findings,we have achieved 97.1% F1-score.The article also discusses the challenges and opportunities of implementing see-through vehicles in real-world scenarios,including technical,regulatory,and user acceptance factors.

关键词： Overtaking safety Augmented reality VANET V2V deep learning

Large-scale spatial data visualization method based on Augmented reality

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虚拟现实与智能硬件（中英文） 2024年第2期6卷 132-147页

作者： Xiaoning QIAO Wenming XIE Xiaodong PENG Guangyun LI Dalin LI Yingyi GUO Jingyi REN Key Laboratory of Electronics and Information Technology for Space Systems National Space Science CenterChinese Academy of SciencesBeijing 100190China University of Chinese Academy of Sciences Beijing 100049China Ordnance Science and Research Academy of China Beijing 100089China

Background A task assigned to space exploration satellites involves detecting the physical environment within a certain space.However,space detection data are complex and abstract.These data are not conducive for researchers'visual perceptions of the evolution and interaction of events in the space environment.Methods A time-series dynamic data sampling method for large-scale space was proposed for sample detection data in space and time,and the corresponding relationships between data location features and other attribute features were established.A tone-mapping method based on statistical histogram equalization was proposed and applied to the final attribute feature data.The visualization process is optimized for rendering by merging materials,reducing the number of patches,and performing other operations.Results The results of sampling,feature extraction,and uniform visualization of the detection data of complex types,long duration spans,and uneven spatial distributions were obtained.The real-time visualization of large-scale spatial structures using Augmented reality devices,particularly low-performance devices,was also investigated.Conclusions The proposed visualization system can reconstruct the three-dimensional structure of a large-scale space,express the structure and changes in the spatial environment using Augmented reality,and assist in intuitively discovering spatial environmental events and evolutionary rules.

关键词： Large-scale spatial data analysis Visual analysis technology Augmented reality 3D reconstruction Space environment

Single-center experience with Knee+^(TM) Augmented reality navigation system in primary total knee arthroplasty

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World Journal of Orthopedics 2024年第3期15卷 247-256页

作者： Evangelos Sakellariou Panagiotis Alevrogiannis Fani Alevrogianni Athanasios Galanis Michail Vavourakis Panagiotis Karampinas Panagiotis Gavriil John Vlamis Stavros Alevrogiannis The 3^(rd)Department of Orthopaedic Surgery National&Kapodistrian University of AthensKAT General HospitalAthens 14561Greece The 1^(st)Department of Orthopaedic Surgery National&Kapodistrian University of AthensAttikon General HospitalAthens 14561Greece Department of Anesthesiology KAT General HospitalAthens 14561Greece Department of Robotic Hip&Knee Orthopaedic Surgery Metropolitan General HospitalAthens 14561Greece

BACKGROUND Computer-assisted systems obtained an increased interest in orthopaedic surgery over the last years,as they enhance precision compared to conventional hardware.The expansion of computer assistance is evolving with the employment of Augmented reality.Yet,the accuracy of Augmented reality navigation systems has not been determined.AIM To examine the accuracy of component alignment and restoration of the affected limb’s mechanical axis in primary total knee arthroplasty(TKA),utilizing an Augmented reality navigation system and to assess whether such systems are conspicuously fruitful for an accomplished knee surgeon.METHODS From May 2021 to December 2021,30 patients,25 women and five men,under-went a primary unilateral TKA.Revision cases were excluded.A preoperative radiographic procedure was performed to evaluate the limb’s axial alignment.All patients were operated on by the same team,without a tourniquet,utilizing three distinct prostheses with the assistance of the Knee+™Augmented reality navigation system in every operation.Postoperatively,the same radiographic exam protocol was executed to evaluate the implants’position,orientation and coronal plane alignment.We recorded measurements in 3 stages regarding femoral varus and flexion,tibial varus and posterior slope.Firstly,the expected values from the Augmented reality system were documented.Then we calculated the same values after each cut and finally,the same measurements were recorded radiolo-gically after the operations.Concerning statistical analysis,Lin’s concordance correlation coefficient was estimated,while Wilcoxon Signed Rank Test was performed when needed.RESULTS A statistically significant difference was observed regarding mean expected values and radiographic mea-surements for femoral flexion measurements only(Z score=2.67,P value=0.01).Nonetheless,this difference was statistically significantly lower than 1 degree(Z score=-4.21,P value<0.01).In terms of discrepancies in the calculations of expected values and controlled measurements,a s

关键词： Augmented reality Orthopedics Total knee arthroplasty Robotics Knee Navigation

Uses of a dedicated 3D reconstruction software with augmented and mixed reality in planning and performing advanced liver surgery and living donor liver transplantation(with videos)

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Hepatobiliary & Pancreatic Diseases International 2022年第5期21卷 455-461页

作者： Deniz Balci Elvan Onur Kirimker Dimitri Aristotle Raptis Yujia Gao Alfred Wei Chieh Kow Department of Surgery Medical Park Goztepe Hastanesi Organ Nakli Merkezi Nisan SokBahce se hir UniversityNo.23 Merdivenkoy KadıkoyIstanbulTurkiye Department of Surgery Ankara UniversityAnkaraTurkiye Clinical Service of HPB Surgery and Liver Transplantation NHS Foundation TrustRoyal Free London HospitalLondonUK Division of Surgery&Interventional Science University College LondonLondonUK Division of Hepatobiliary&Pancreatic Surgery Department of SurgeryNational University of SingaporeSingapore Liver Transplant Program National University Center for Organ Transplantation(NUCOT)National University Health SystemSingapore

The development of digital intelligent diagnostic and treatment technology has opened countless new opportunities for liver surgery from the era of digital anatomy to a new era of digital diagnostics,virtual surgery simulation and using the created scenarios in real-time surgery using mixed reality.In this article,we described our experience on developing a dedicated 3 dimensional visualization and reconstruction software for surgeons to be used in advanced liver surgery and living donor liver transplantation.Furthermore,we shared the recent developments in the field by explaining the outreach of the software from virtual reality to Augmented reality and mixed reality.

关键词： Living donor liver transplantation 3D reconstruction software 3D volumetry Precision medicine Augmented reality Mixed reality

Defect inspection of indoor components in buildings using deep learning object detection and Augmented reality

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Earthquake Engineering and Engineering Vibration 2023年第1期22卷 41-54页

作者： Shun-Hsiang Hsu Ho-Tin Hung Yu-Qi Lin Chia-Ming Chang Department of Civil and Environmental Engineering University of Illinois at Urbana-ChampaignUSA Department of Civil Engineering Taiwan University(NTU)TaiwanChina

Visual inspection is commonly adopted for building operation,maintenance,and safety.The durability and defects of components or materials in buildings can be quickly assessed through visual inspection.However,implementations of visual inspection are substantially time-consuming,labor-intensive,and error-prone because useful auxiliary tools that can instantly highlight defects or damage locations from images are not available.Therefore,an advanced building inspection framework is developed and implemented with Augmented reality(AR)and real-time damage detection in this study.In this framework,engineers should walk around and film every corner of the building interior to generate the three-dimensional(3D)environment through ARKit.Meanwhile,a trained YOLOv5 model real-time detects defects during this process,even in a large-scale field,and the defect locations indicating the detected defects are then marked in this 3D environment.The defects areas can be measured with centimeter-level accuracy with the light detection and ranging(LiDAR)on devices.All required damage information,including defect positions and sizes,is collected at a time and can be rendered in the 2D and 3D views.Finally,this visual inspection can be efficiently conducted,and the previously generated environment can also be loaded to re-localize existing defect marks for future maintenance and change observation.Moreover,the proposed framework is also implemented and verified by an underground parking lot in a building to detect and quantify surface defects on concrete components.As seen in the results,the conventional building inspection is significantly improved with the aid of the proposed framework in terms of damage localization,damage quantification,and inspection efficiency.

关键词： visual inspection damage detection Augmented reality damage quantification deep learning

DeepRadiation:An intelligent Augmented reality platform for predicting urban energy performance just through 360 panoramic streetscape images utilizing various deep learning models

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Building Simulation 2023年第3期16卷 499-510页

作者： Ali Nakhaee Arefe Paydar Department of Architecture Architecture SchoolCollege of Fine ArtsUniversity of TehranTehran ***Iran

Urban energy simulation is critical for understanding and managing energy performance in cities.In this research,we design a novel framework called DeepRadiation,to enable automatic urban environmental performance prediction.By incorporating deep learning strategies,DeepRadiation predicts solar radiation on an urban scale using just panoramic streetscape images without any 3D modeling and simulation.New York City was chosen as the case study for this research.DeepRadiation is comprised of three different deep learning models organized into two stages.The first stage,named DeepRadiation modeling,serves as the framework's brain.At this stage,solar radiation analysis was performed using a Pix2Pix model,a type of conditional generative adversarial networks(GANs).After extracting GIS data and performing energy simulation analysis to prepare the dataset,the Pix2Pix model was trained on 10000 paired panoramic depth images of streetscapes with only building blocks and related panoramic images of streetscapes with only solar radiation analysis.Two GAN generator evaluation measures named qualitative evaluation and quantitative evaluation were used to validate the trained Pix2Pix model.Both demonstrated high levels of accuracy(qualitative evaluation:93%,quantitative evaluation:89%).DeepRadiation application as the DeepRadiation's sescond stage is the framework's eyes.At this stage,two convolutional neural network(CNN)models(DeepLabv3 and MiDaS)were used to perform computer vision tasks on panoramic streetscape images,such as semantic segmentation and depth estimation.The DeepRadiation application stage allows urban designers,architects,and urban policymakers to use the DeepRadiation framework and experience the final output via Augmented reality.

关键词： automating urban energy simulation solar radiation analysis deep learning Pix2Pix computer vision Augmented reality

ARCosmetics:a real-time Augmented reality cosmetics try-on system

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Frontiers of Computer Science 2023年第4期17卷 15-28页

作者： Shan AN Jianye CHEN Zhaoqi ZHU Fangru ZHOU Yuxing YANG Yuqing MA Xianglong LIU Haogang ZHU Tech.&Data Center *** Inc.Beijing 100176China State Key Lab of Software Development Environment Beihang UniversityBeijing 100191China

A virtual cosmetics try-on system provides a realistic try-on experience for consumers and helps them efficiently choose suitable cosmetics.In this article,we propose a real-time Augmented reality virtual cosmetics try-on system for smartphones(ARCosmetics),taking speed,accuracy,and stability into consideration at each step to ensure a better user experience.A novel and very fast face tracking method utilizes the face detection box and the average position of facial landmarks to estimate the faces in continuous frames.A dynamic weight Wing loss is introduced to assign a dynamic weight to every landmark by the estimated error during training.It balances the attention between small,medium,and large range error and thus increases the accuracy and robustness.We also designed a weighted average method to utilize the information of the adjacent frame for landmark refinement,guaranteeing the stability of the generated landmarks.Extensive experiments conducted on a large 106-point facial landmark dataset and the 300-VW dataset demonstrate the superior performance of the proposed method compared to other state-of-the-art methods.We also conducted user satisfaction studies further to verify the efficiency and effectiveness of our ARCosmetics system.

关键词： facial landmark localization face tracking stabilization Augmented reality virtual try-on

Visualization of real-time displacement time history superimposed with dynamic experiments using wireless smart sensors and Augmented reality

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Earthquake Engineering and Engineering Vibration 2023年第3期22卷 573-588页

作者： Marlon Aguero Derek Doyle David Mascarenas Fernando Moreu Department of Civil Construction and Environmental EngineeringUniversity of New MexicoCentennial Engineering Center 3056MSC011070210 University Blvd NEAlbuquerqueNM 87131USA Air Force Research Laboratory Space Vehicles DirectorateKirtland Air Force BaseAlbuquerqueNM 87117USA Engineering Institute Los Alamos National LaboratoryLos AlamosNM 8754USA

Wireless smart sensors(WSS)process field data and inform inspectors about the infrastructure health and safety.In bridge engineering,inspectors need reliable data about changes in displacements under loads to make correct decisions about repairs and replacements.Access to displacement information in the field and in real-time remains a challenge as inspectors do not see the data in real time.Displacement data from WSS in the field undergoes additional processing and is seen at a different location.If inspectors were able to see structural displacements in real-time at the locations of interest,they could conduct additional observations,creating a new,information-based,decision-making reality in the field.This paper develops a new,human-centered interface that provides inspectors with real-time access to actionable structural data during inspection and monitoring enhanced by Augmented reality(AR).It summarizes and evaluates the development and validation of the new human-infrastructure interface in laboratory experiments.The experiments demonstrate that the interface that processes all calculations in the AR device accurately estimates dynamic displacements in comparison with the laser.Using this new AR interface tool,inspectors can observe and compare displacement data,share it across space and time,visualize displacements in time history,and understand structural deflection more accurately through a displacement time history visualization.

关键词： wireless smart sensor monitoring Augmented reality displacement acceleration human-infrastructure interface