Bibliometric review of visual computing in the construction industry

In the construction area,visuals such as drawings,photos,videos,and 3D models,play a significant role in the design,build and maintenance of a facility,bringing efficiency to generate,transfer,and store information.Advanced visual computing techniques facilitate the understanding of design contents,work plans,and other types of information shared in the construction industry.Automatic visual data collection and analysis provide many possibilities to the construction industry and a large number of works have investigated how visual computing can improve construction management processes and other problems in the construction area.However,a comprehensive literature review is needed.This study uses bibliometric approaches to review the works published to date,and analyses the development of knowledge,significant research results,and trends.The purpose of this study is to help newcomers to this research field understand knowledge structure and formulate research directions,thereby enhancing knowledge development.From this study,it can be concluded that computer vision is a key axis of improvement.Moreover,building information modeling,laser scanning,and other visualizationrelated techniques are also important in advancing the construction area.

Robustness optimization for rapid prototyping of functional artifacts based on visualized computing digital twins

This study presents a robustness optimization method for rapid prototyping(RP)of functional artifacts based on visualized computing digital twins(VCDT).A generalized multiobjective robustness optimization model for RP of scheme design prototype was first built,where thermal,structural,and multidisciplinary knowledge could be integrated for visualization.To implement visualized computing,the membership function of fuzzy decision-making was optimized using a genetic algorithm.Transient thermodynamic,structural statics,and flow field analyses were conducted,especially for glass fiber composite materials,which have the characteristics of high strength,corrosion resistance,temperature resistance,dimensional stability,and electrical insulation.An electrothermal experiment was performed by measuring the temperature and changes in temperature during RP.Infrared thermographs were obtained using thermal field measurements to determine the temperature distribution.A numerical analysis of a lightweight ribbed ergonomic artifact is presented to illustrate the VCDT.Moreover,manufacturability was verified based on a thermal-solid coupled finite element analysis.The physical experiment and practice proved that the proposed VCDT provided a robust design paradigm for a layered RP between the steady balance of electrothermal regulation and manufacturing efficacy under hybrid uncertainties.

Geometrical Modeling by NURBS Surface and RCS Computing by Visualization for Complex Targets

A novel approach to compute the high frequency radar cross-section (RCS) of complex targets is described in this paper.From the three views or the sectional views of the target, target is geometrically modeled by non-uniform rational B-spline (NURBS) parametric surfaces using the software CNFEOV developed by oneself which constructs NURBS representation of complex target from engineering orthographic views. RCS is obtained through PO, PTD, MEC and IBC techniques. When calculating RCS of the target, it is necessary to get the unit normal vector to surface illumi- nated by radar and the value Z which is the distance from the point on the surface to radar. ln this novel approach, the unit normal vector to the surface can be obtained either by the Phong rendering model, in which the color components (RGB) of every pixel on the image are equal to the coordinate components of the normal, or by the NURBS expressions. The value Z can be achieved by software or hardware Z-buffer. The effects of the size of image on the RCS of target are discussed and the correct method is recommended. The RCS of the perfect conducting sphere, cylinder and dihedral as well as the coated cylinder, as some examples, are computed. The accuracy of the method is verified by comparing the numerical results with those obtained by using other methods.

Integration system research and development for three-dimensional laser scanning information visualization in goaf

An integration processing system of three-dimensional laser scanning information visualization in goaf was developed. It is provided with multiple functions, such as laser scanning information management for goaf, cloud data de-noising optimization, construction, display and operation of three-dimensional model, model editing, profile generation, calculation of goaf volume and roof area, Boolean calculation among models and interaction with the third party soft ware. Concerning this system with a concise interface, plentiful data input/output interfaces, it is featured with high integration, simple and convenient operations of applications. According to practice, in addition to being well-adapted, this system is favorably reliable and stable.

A language to analyze, describe, and explore collections of visual art

A vast quantity of art in existence today is inaccessible to individuals.If people want to know the different types of art that exist,how individual works are connected,and how works of art are interpreted and discussed in the context of other works,they must utilize means other than simply viewing the art.Therefore,this paper proposes a language to analyze,describe,and explore collections of visual art(LadeCA).LadeCA combines human interpretation and automatic analyses of images,allowing users to assess collections of visual art without viewing every image in them.This paper focuses on the lexical base of LadeCA.It also outlines how collections of visual art can be analyzed,described,and explored using a LadeCA vocabulary.Additionally,the relationship between LadeCA and indexing systems,such as ICONCLASS or AAT,is demonstrated,and ways in which LadeCA and indexing systems can complement each other are highlighted.

Visualization Techniques in Electromagnetic Engineering

It briefly describes the techniques of Visualization in Scientific Computation (ViSC). Combining Open GL, a 3D graphic library, we discuss and analyze some visualization techniques in electromagnetic engineering.

VISUALIZATION OF THREE-DIMENSIONAL DATA FIELD AND ITS APPLICATION IN MACHINE TESTING

In order to realize visualization of three-dimensional data field （TDDF） in instrument, two methods of visualization of TDDF and the usual manner of quick graphic and image processing are analyzed. And how to use OpenGL technique and the characteristic of analyzed data to construct a TDDF, the ways of reality processing and interactive processing are described. Then the medium geometric element and a related realistic model are constructed by means of the first algorithm. Models obtained for attaching the third dimension in three-dimensional data field are presented. An example for TDDF realization of machine measuring is provided. The analysis of resultant graphic indicates that the three-dimensional graphics built by the method developed is featured by good reality, fast processing and strong interaction

Hierarchical Visual Analysis and Steering Framework for Astrophysical Simulations

A framework for accelerating modern long-running astrophysical simulations is presented, which is based on a hierarchical architecture where computational steering in the high-resolution run is performed under the guide of knowledge obtained in the gradually refined ensemble analyses. Several visualization schemes for facilitating ensemble management, error analysis, parameter grouping and tuning are also integrated owing to the pluggable modular design. The proposed approach is prototyped based on the Flash code, and it can be extended by introducing userdefined visualization for specific requirements. Two real-world simulations, i.e., stellar wind and supernova remnant, are carried out to verify the proposed approach.

Next Generation Semantic and Spatial Joint Perception——Neural Metric-Semantic Understanding

Efficient perception of the real world is a long-standing effort of computer vision.Mod⁃ern visual computing techniques have succeeded in attaching semantic labels to thousands of daily objects and reconstructing dense depth maps of complex scenes.However,simultaneous se⁃mantic and spatial joint perception,so-called dense 3D semantic mapping,estimating the 3D ge⁃ometry of a scene and attaching semantic labels to the geometry,remains a challenging problem that,if solved,would make structured vision understanding and editing more widely accessible.Concurrently,progress in computer vision and machine learning has motivated us to pursue the capability of understanding and digitally reconstructing the surrounding world.Neural metric-se⁃mantic understanding is a new and rapidly emerging field that combines differentiable machine learning techniques with physical knowledge from computer vision,e.g.,the integration of visualinertial simultaneous localization and mapping(SLAM),mesh reconstruction,and semantic un⁃derstanding.In this paper,we attempt to summarize the recent trends and applications of neural metric-semantic understanding.Starting with an overview of the underlying computer vision and machine learning concepts,we discuss critical aspects of such perception approaches.Specifical⁃ly,our emphasis is on fully leveraging the joint semantic and 3D information.Later on,many im⁃portant applications of the perception capability such as novel view synthesis and semantic aug⁃mented reality(AR)contents manipulation are also presented.Finally,we conclude with a dis⁃cussion of the technical implications of the technology under a 5G edge computing scenario.

Transformers in computational visual media:A survey

Transformers,the dominant architecture for natural language processing,have also recently attracted much attention from computational visual media researchers due to their capacity for long-range representation and high performance.Transformers are sequence-to-sequence models,which use a selfattention mechanism rather than the RNN sequential structure.Thus,such models can be trained in parallel and can represent global information.This study comprehensively surveys recent visual transformer works.We categorize them according to task scenario:backbone design,high-level vision,low-level vision and generation,and multimodal learning.Their key ideas are also analyzed.Differing from previous surveys,we mainly focus on visual transformer methods in low-level vision and generation.The latest works on backbone design are also reviewed in detail.For ease of understanding,we precisely describe the main contributions of the latest works in the form of tables.As well as giving quantitative comparisons,we also present image results for low-level vision and generation tasks.Computational costs and source code links for various important works are also given in this survey to assist further development.

Toward Human-centered XAIin Practice:A survey

Human adoption of artificial intelligence(AI)technique is largely hampered because of the increasing complexity and opacity of AI development.Explainable AI(XAI)techniques with various methods and tools have been developed to bridge this gap between high-performance black-box AI models and human understanding.However,the current adoption of XAI technique stil lacks"human-centered"guidance for designing proper solutions to meet different stakeholders'needs in XAI practice.We first summarize a human-centered demand framework to categorize different stakeholders into five key roles with specific demands by reviewing existing research and then extract six commonly used human-centered XAI evaluation measures which are helpful for validating the effect of XAI.In addition,a taxonomy of XAI methods is developed for visual computing with analysis of method properties.Holding clearer human demands and XAI methods in mind,we take a medical image diagnosis scenario as an example to present an overview of how extant XAI approaches for visual computing fulfil stakeholders'human-centered demands in practice.And we check the availability of open-source XAI tools for stakeholders'use.This survey provides further guidance for matching diverse human demands with appropriate XAI methods or tools in specific applications with a summary of main challenges and future work toward human-centered XAI in practice.

ARSlice:Head-Mounted Display Augmented with Dynamic Tracking and Projection

Computed tomography(CT)generates cross-sectional images of the body.Visualizing CT images has been a challenging problem.The emergence of the augmented and virtual reality technology has provided promising solutions.However,existing solutions suffer from tethered display or wireless transmission latency.In this paper,we present ARSlice,a proof-of-concept prototype that can visualize CT images in an untethered manner without wireless transmission latency.Our ARSlice prototype consists of two parts,the user end and the projector end.By employing dynamic tracking and projection,the projector end can track the user-end equipment and project CT images onto it in real time.The user-end equipment is responsible for displaying these CT images into the 3D space.Its main feature is that the user-end equipment is a pure optical device with light weight,low cost,and no energy consumption.Our experiments demonstrate that our ARSlice prototype provides part of six degrees of freedom for the user,and a high frame rate.By interactively visualizing CT images into the 3D space,our ARSlice prototype can help untrained users better understand that CT images are slices of a body.