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This paper aims to propose a novel real-time three-dimensional (3D) model-based work-piece tracking method with monocular camera for high-precision assembly. Tracking of 3D work-pieces with real-time speed is becoming more and more important for some industrial tasks, such as work-pieces grasping and assembly, especially in complex environment.

A three-step process method was provided, i.e. the offline static global library generation process, the online dynamic local library updating and selection process and the 3D work-piece localization process. In the offline static global library generation process, the computer-aided design models of the work-piece are used to generate a set of discrete two-dimensional (2D) hierarchical views matching libraries. In the online dynamic library updating and selection process, the previous 3D location information of the work-piece is used to predict the following location range, and a discrete matching library with a small number of 2D hierarchical views is selected from dynamic local library for localization. Then, the work-piece is localized with high-precision and real-time speed in the 3D work-piece localization process.

The method is suitable for the texture-less work-pieces in industrial applications.

The small range of the library enables a real-time matching. Experimental results demonstrate the high accuracy and high efficiency of the proposed method.

This paper aims to propose a real-time augmented reality (AR)-based assembly assistance system using a coarse-to-fine marker-less tracking strategy. The system automatically adapts to tracking requirement when the topological structure of the assembly changes after each assembly step.

The prototype system’s process can be divided into two stages: the offline preparation stage and online execution stage. In the offline preparation stage, planning results (assembly sequence, parts position, rotation, etc.) and image features [gradient and oriented FAST and rotated BRIEF (ORB)features] are extracted automatically from the assembly planning process. In the online execution stage, too, image features are extracted and matched with those generated offline to compute the camera pose, and planning results stored in XML files are parsed to generate the assembly instructions for manipulators. In the prototype system, the working range of template matching algorithm, LINE-MOD, is first extended by using depth information; then, a fast and robust marker-less tracker that combines the modified LINE-MOD algorithm and ORB tracker is designed to update the camera pose continuously. Furthermore, to track the camera pose stably, a tracking strategy according to the characteristic of assembly is presented herein.

The tracking accuracy and time of the proposed marker-less tracking approach were evaluated, and the results showed that the tracking method could run at 30 fps and the position and pose tracking accuracy was slightly superior to ARToolKit.

The main contributions of this work are as follows: First, the authors present a coarse-to-fine marker-less tracking method that uses modified state-of-the-art template matching algorithm, LINE-MOD, to find the coarse camera pose. Then, a feature point tracker ORB is activated to calculate the accurate camera pose. The whole tracking pipeline needs, on average, 24.35 ms for each frame, which can satisfy the real-time requirement for AR assembly. On basis of this algorithm, the authors present a generic tracking strategy according to the characteristics of the assembly and develop a generic AR-based assembly assistance platform. Second, the authors present a feature point mismatch-eliminating rule based on the orientation vector. By obtaining stable matching feature points, the proposed system can achieve accurate tracking results. The evaluation of the camera position and pose tracking accuracy result show that the study’s method is slightly superior to ARToolKit markers.

The purpose of this research is to investigate a new approach with its supporting building information modelling (BIM) + augmented reality (AR) tool to enhance architectural visualisation in building life cycle. Traditional approaches to visualise architectural design concentrate on static pictures or three-dimensional (3D) scale models which cause problems, such as expensive design evolution, lack of stakeholders’ communication and limited reusability. The 3D animated fly-throughs still occur on a computer screen in two-dimensions and seem cold and mechanical, unless done with advanced production software.

The method of this research included case study and interview. It was, first, stated, from the building process perspective, how the BIM + AR for Architectural Visualisation System (BAAVS) was realised by integrating two types of visualisation techniques: BIM and AR, and four stages of building life cycle. Then the paper demonstrated four case studies to validate the BAAVS. Finally, four interviews were made with each case manager and team members to collect feedback on utilising BAAVS technology. Questions were asked in the areas of benefits, drawbacks and technical limitations with respect to BAAVS.

Feedback from the stakeholders involved in the four cases indicated that BAAVS was useful and efficient to visualise architectural design and communicate with each other.

This paper demonstrates BAAVS that integrated BIM and AR into architectural visualisation. The system supports an innovative performance that allows: designers to put virtual building scheme in physical environment; owners to gain an immersive and interactive experience; and property sellers to communicate with customers efficiently.

The purpose of this paper is to present an approach to improve the accuracy of estimating feature points of human body on a vision‐based motion capture system (MCS) by using the variable‐density self‐organizing map (VDSOM).

The VDSOM is a kind of self‐organizing map (SOM) and has an ability to learn training samples incrementally. The authors let VDSOM learn 3D feature points of human body when the MCS succeeded in estimating them correctly. On the other hand, one or more 3D feature point could not be estimated correctly, the VDSOM is used for the other purpose. The SOM including VDSOM has an ability to recall a part of weight vector which have learned in the learning process. This ability is used to recall correct patterns and complement such incorrect feature points by replacing such incorrect feature points with them.

Experimental results show that the approach is effective for estimation of human posture robustly compared with the other methods.

The proposed approach is interesting for the collaboration between an MCS and an incremental learning.

This paper presents the design and validation of a universal 6D seam tracking system that reduces the need of accurate robot trajectory programming and geometrical databases in robotic laser scanning. The 6D seam tracking system was developed in the flexible unified simulation environment, integrating software prototyping with mechanical virtual prototyping, based on physical experiments. The validation experiments showed that this system was both robust and reliable and should be able to manage a radius of curvature less than 200 mm. In the pre‐scanning mode, a radius of curvature down to 2 mm was managed for pipe intersections at 3 scans/mm, using a laser scanner with an accuracy of 0.015 mm.

This paper aims to target tracking in the marine environment is typically obtained by considering the measurement parameters like frequency, elevation and bearing. Marine environmental surveillance provides critical information and assistance for the exploitation and maintenance of marine resources.

With the use of intelligent sensor techniques like Hull-mounted and towed array sensors, convenient, precise and dependable three-dimensional (3D) underwater target tracking is introduced.

This research investigates a method to develop a reliable Unscented Kalman Filter (UKF) algorithm for enhanced underwater target tracking in a 3D scenario by using bearing, frequency and elevation measurements. In applications for underwater target tracking, uncertainty and inaccuracies are typically described by using Gaussian additive noise.

The proposed UKF algorithm is tested and analyzed using 100 Monte Carlo simulations with the Gaussian generated noise.

Interface distinct two-phase computational fluid dynamics (CFD) simulations require accurate tracking in surface curvature, surface area and volume fraction data to precisely calculate effects such as surface tension, interphase momentum and interphase heat and mass transfer exchanges. To attain a higher level of accuracy in two-phase flow CFD simulations, the intersection marker (ISM) method was developed. The ISM method has cell-by-cell remeshing capability that is volume conservative, maintains surface continuity and is suited for the tracking of interface deformation in transient two-phase flow simulations. Studies of isothermal single bubbles rising in quiescent water were carried out to test the ISM method for two-phase flow simulations.

The ISM method is a hybrid Lagrangian–Eulerian front tracking algorithm which can model an arbitrary three-dimensional surface within an array of cubic control volumes. Fortran95 was used to implement the ISM method, which resulted in approximately 25,000+ lines of written code and comments. To demonstrate the feasibility of the ISM algorithm for two-phase flow simulations, the ISM algorithm was coupled with an in-house CFD code, which was modified to simulate two-phase flows using a single fluid formulation. The constitutional equations incorporated terms of variable density and viscosity. In addition, body force source terms were included in the momentum equation to account for surface tension and buoyancy effects.

The performance of two-phase flow simulations was benchmarked against experimental data for four air/water bubbles with 1, 2.5, 5 and 10 mm of diameter rising in quiescent fluid. A variety of bubble sizes were tested to demonstrate the accuracy of the ISM interface tracking method. The results attained were in close agreement with experimental observations.

The results obtained show that the ISM method is a viable means for interface tracking of two-phase flow CFD simulations. Other applications of the ISM method include simulations of solid–fluid interaction and other immersed boundary flow problems.

The ISM method is a novel approach to front tracking, and the results shown are original in content.

This paper primarily aims to focus on a review of convolutional neural network (CNN)-based eye control systems. The performance of CNNs in big data has led to the development of eye control systems. Therefore, a review of eye control systems based on CNNs is helpful for future research.

In this paper, first, it covers the fundamentals of the eye control system as well as the fundamentals of CNNs. Second, the standard CNN model and the target detection model are summarized. The eye control system’s CNN gaze estimation approach and model are next described and summarized. Finally, the progress of the gaze estimation of the eye control system is discussed and anticipated.

The eye control system accomplishes the control effect using gaze estimation technology, which focuses on the features and information of the eyeball, eye movement and gaze, among other things. The traditional eye control system adopts pupil monitoring, pupil positioning, Hough algorithm and other methods. This study will focus on a CNN-based eye control system. First of all, the authors present the CNN model, which is effective in image identification, target detection and tracking. Furthermore, the CNN-based eye control system is separated into three categories: semantic information, monocular/binocular and full-face. Finally, three challenges linked to the development of an eye control system based on a CNN are discussed, along with possible solutions.

This research can provide theoretical and engineering basis for the eye control system platform. In addition, it also summarizes the ideas of predecessors to support the development of future research.

The purpose of this paper is to present a methodology that integrates design and assembly planning in an augmented reality (AR) environment. Intuitive bare-hand interactions (BHIs) and a combination of virtual and real objects are used to perform design and assembly tasks. Ergonomics and other assembly factors are analysed during assembly evaluation.

An AR design and assembly (ARDnA) system has been developed to implement the proposed methodology. For design generation, 3D models are created and combined together like building blocks, taking into account the product assembly in the early design stage. Detailed design can be performed on the components and manual assembly process is simulated to evaluate the assembly design.

A case study of the design and assembly of a toy car is conducted to demonstrate the application of the methodology and system.

The system allows the users to consider the assembly of a product when generating the design of the components. BHI allows the users to create and interact with the virtual modes with their hands. Assembly evaluation is more realistic and takes into consideration the ergonomics issues during assembly.

The system synthesizes AR, BHI and a CAD software to provide an integrated approach for design and assembly planning, intuitive and realistic interaction with virtual models and holistic assembly evaluation.

Rapid prototyping and three-dimensional (3D) printing allows the direct creation of objects from 3D computer-aided design files. To identify the effects 3D printing may have on student experiences and the learning of the design process, students were asked to create a design and create a prototype of that design.

This study follows an experimental design involving four total courses of interior design students. After conceptualizing a design, students were randomly selected to either create the prototype by hand or given access to 3D printing equipment. The models were graded by three subject experts using a rubric that focused on three key aspects of the model project, namely, craftsmanship, design quality and scale (proportion).

All three measures produced significant mean differences with a medium effect size when comparing the 3D printed models to the traditionally built models. Additional observations provided insights into the design processes approached by students using hand-constructed and 3D printed modeling. The most notable difference was the propensity for curved and rectilinear shapes by available design technologies.

The experiment showed that the design technology (3D printing) did have an impact on the designs students conceptualized. This suggests that students do connect ideation to implementation, and the availability of enabling technology impacts the design process. This research was conducted in an interior design environment and consists of primarily female students. The experimental research may be limited to design programs with similar student populations and levels of exposure to various design technologies.

This research is designed to provide instructors and programs valuable information when looking at implementing new design technologies into the curriculum. Instructors are made aware that new design technologies do impact student design strategies. Additionally, although certain design technologies allow for revisions, it was apparent that students continued to be resistant to revise their initial models suggesting instructors prepare to address this issue in instruction.

There is a strong body of research indicating inequality in education where students have differing access to technologies in schools. This research shows that 3D printing, similar to many technologies in education, can impact the cognitive processes of content being learned.

There is limited research on how design technologies impact design cognition and the experiences of design students. This paper looked specifically at one design technology (3D printing/rapid prototyping) and how it impacts the processes and quality of design, in addition to the quality of design products (prototypes or models). Research such as this provides instructors and faculty members an insight into how design technologies impact their curriculum.