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This paper aims to propose a system to acquire images automatically for digital reconstruction of heritage artifacts using a six-degree of freedom industrial manipulator.

A virtual environment is created using Robot Studio® software to integrate the trajectory and differential motion of the robot manipulator and the motion of camera while acquiring images. A new area similarity matrix method is proposed to reduce the number of images required for digital reconstruction using Autodesk Recap® software. Real-time experiments have been performed using objects such as minion, ultimaker robot and cube. Evaluation of the digital reconstruction is conducted using the contour area matching method.

The number of images required for reconstruction based on area similarity matrix method is reduced to 63 per cent when compared with the random selection method. Quality parameters such as surface area, volume, number of defect holes, vertices and faces are enhanced for the proposed method.

Digital reconstruction of large-sized heritage artifacts cannot be performed in this setup. But this can be overcome by fixing the manipulator on a mobile platform or overhead crane. This paper does not discuss the reconstruction of partially damaged heritage artifacts, which could be accomplished based on deep learning techniques.

Using this approach, off-the-shelf heritage artifacts and large-scale objects can be reconstructed digitally with a minimum number of images and without compromising the quality of original models.

To the best of the authors’ knowledge, area similarity-based approach in 3D digital reconstruction by coupling the kinematics of an industrial manipulator and camera is proposed for the first time. A fully automated digital reconstruction technology to preserve valuable heritage artifacts has been developed. It also highlights the space constraints of the industrial manipulator in digital reconstruction.

The purpose of this paper is to introduce a significant modification of the sensitivity maps calculation process using electric field distribution analysis. A sensitivity matrix is typically a crucial part of a deterministic image reconstruction process in a three-dimensional capacitance tomography (3D ECT) and strictly decides about a final image quality. Commonly used sensitivity matrix computation methods mostly provide acceptable results and additionally allow to perform a recalculation of sensitivity maps according to the changing permittivity distribution.

The new “tunnel-based” algorithm is proposed which traces the surfaces constructed along the electric field lines. The new solution is developed and tested using experimental data.

To fully validate the new technique both linear and non-linear image reconstruction processes were performed and the criteria of image error estimation were discussed. This paper discusses some preliminary results of the image reconstruction process using the new proposed algorithm. As a result of this research, an increased accuracy of the new method is proved.

The presented results of image reconstruction with new sensitivity matrix in comparison with the classic matrix proved that the new solution is able to improve the convergence and stability of image reconstruction process for 3D ECT imaging.

This study aims to develop an optimized 3D laser point reconstruction using Descent Gradient algorithm. Precise and accurate reconstruction of 3D laser point cloud of the complex environment/object is a key solution for many industries such as construction, gaming, automobiles, aerial navigation, architecture and automation. A 2D laser scanner along with a servo motor/pan tilt/inertial measurement unit is used for generating 3D point cloud (either environment/object or both) by acquiring the real-time data from sensors. However, while generating the 3D laser point cloud, various problems related to time synchronization problem between laser and servomotor and torque variation in servomotors arise, which causes misalignment in stacking the 2D laser scan for generating the 3D point cloud of the environment. Because of the misalignment in stacking, the 2D laser scan corresponding to the erroneous angular and position information by the servomotor and the 3D laser point cloud become distorted in terms of inconsistency for measuring the dimension of the objects.

This paper addresses a modified 3D laser system assembled from a 2D laser scanner coupled with a servomotor (dynamixel motor) for developing an efficient 3D laser point cloud with the implementation of an optimization technique: descent gradient filter (DGT). The proposed approach reduces the cost function (error) in the angular and position coordinates of the servo motor caused because of torque variation and time synchronization, which resulted in enhancing the accuracy in 3D point cloud mapping for the accurate measurement of the object’s dimensions.

Various real-world experiments are performed with the proposed DGT filter linked with laser scanner and servomotor and an improvement of 6.5 per cent in measuring the accurate dimension of object is obtained while comparing with conventional approaches for generating a 3D laser point cloud.

This proposed technique may be applicable for various industrial applications that are based on robotics arms (such as painting, welding and cutting) in the automobile industry, the optimized measurement of object, efficient mobile robot navigation, precise 3D reconstruction of environment/object in construction, architecture applications, airborne applications and aerial navigation.

The purpose of this paper is to develop a mathematical tool and an experimental platform to be able to reconstruct thermal plasmas in three dimensions (3D) in order to characterize 3D plasma and to validate models in 3D. Indeed, a lack of experimental data allowing validating 3D models exists.

The paper is realized with a transferred argon arc configuration. The 3D character is due to the form of the cathode electrode. The reactor design is defined by a previous theoretical study. This previous paper has shown that tomographic method through four views allows reconstructing 3D object. The light emitted by the plasma along four directions (four windows) is so spectrally resolved and treated by a multiplicative algebraic reconstruction technique algorithm. Following the emissivity profiles, two methods are used, the absolute line intensity method, and for an out off‐axis maximum of the emissivity the Folwer Milne method.

After a validating approach of the optical measurements in symmetrical configuration using Abel inversion, the reconstructed method is used. The results show the possibility of the tomographic method spectrally and spatially resolved to be applied to thermal plasma in order to characterise the medium and to validate the 3D models. The plasma medium is well described with a spatial resolution equal to 0.2 mm.

The method is applicable to thermal plasma presenting high emissivity. Even if the theoretical reconstruction method is applied to low temperatures or to theoretical plasma presenting out off‐axis of emissivity, future researches need to be performed to analyse the ability of the method to spatially resolve the areas presenting low emissivity.

The paper's originality can be demonstrated by the poor number of studies in thermal plasma reconstruction in 3D. Studies on plasma imaging can be found but not spectrally resolved. The special care on the spectral acquisition along the plasma radius combined with the tomographic reconstruction method lead to the originality of this paper.

The purpose of the paper was to present a specific case study of how 3D printing was introduced in the chest wall construction process of a specific patient with unique medical condition. A life-size 3D model of the patient’s chest wall was 3D printed for pre-surgical planning. The intent was to eliminate the need for operative exposure to map the pathological area. The model was used for preoperative visualization and formation of a 1-mm thick titanium plate implant, which was placed in the patient during chest wall reconstructive surgery. The purpose of the surgery was to relive debilitating chronic pain due to right scapular entrapment.

The patient was born with a twisted spine. Over time, it progressed to severe and debilitating scoliosis, which required the use of a thoracic brace. Computerized tomography (CT) data were converted to a 3D printed model. The model was used to size and form a 1-mm thick titanium plate implant. It was also used to determine the ideal location for placement of the plate during thoracotomy preoperatively.

The surgery, aided by the model, was successful and resulted in a significantly smaller incision. The techniques reduced invasiveness and enabled the doctors to conduct the procedure efficiently and decreased surgery time. The patient experienced relief of the chronic debilitating pain and no longer need the thoracic brace.

The 3D model facilitated pre-operative planning and modeling of the implant. It also enabled accurate incision locations of the thoracotomy site and placement of the implant. Although chest wall reconstruction surgeries have been undertaken, this paper documents a specific case study of chest wall construction fora specific patient with unique pathological conditions.

Aims to make a mobile robot able to build accurate 2D and 3D models of its environment while navigating autonomously.

2D map building is performed using a laser range scanner. The map is used by the robot to both localize itself and recognize places already explored. This is the well‐known simultaneous localization and mapping (SLAM) problem. 3D model reconstruction, instead, uses computer vision techniques based on feature extraction and matching.

The experimental results illustrate the validity and accuracy of the reconstructed maps of the environment and enable the robot to navigate autonomously in indoor environments, such as museums, hospitals, airports, offices and so on. Such a robot can play a major role in different tasks such as surveillance, image‐based rendering, remote fruition of hardly accessible sites, monitoring and maintenance applications, reverse engineering in construction. In these areas accurate 3D models in addition to 2D maps can convey a lot of very useful information.

The main contribution of the paper is an interesting integration of different algorithms in an experimental platform that performs 2D map building using a laser range scanner, autonomous navigation and 3D reconstruction of the areas of particular interest.

Virtual design of contemporary and historical clothes is a very intensive and developing area of science that can be considered as a bridge between costume heritage and modern way of its presentation by means of CAD. The purpose of this paper is to apply 2D and 3D existing CAD for virtual reconstruction of the very specific kind of women’s clothes such as a side-saddle riding habit (RH) used in 1875–1915.

The construction of RH was adapted to the aesthetic rules of the mentioned time, ergonomic posture of a woman sitting on a horse, surface of the horse’s body which the woman is sitting on. For the new method, the huge databases were obtained after analyzing the historical pattern manuals and features of pattern blocks used, possible postures of riding, construction of RH and converting it into virtual system “avatar – RH.” To reconstruct the side-saddle RH in virtual reality, the images dated 1887 and authentic pattern blocks were used. Special attention has been given to the topology of contacting areas existing between the sitting woman and “shaped” riding skirt and to the method of presenting it by means of special points combination.

The authors have developed a new method of virtual reconstruction of an RH that is based on automatic consideration of all joining elements such as “shaped” riding skirt, avatar and its ergonomic posture. The new approach allows reconstruction of the clothes in virtual reality in three ways: by using the real skirts, the historical pattern blocks or pictures.

The results obtained allow increased possibilities of virtual reconstruction and include in the list new objects of engineering achievements of the nineteenth century such as the side-saddle RH. This study should help researchers and practical specialists to recreate and save the historical treasure in a digital way.

This paper aims to propose an automatic imaging network design to improve the efficiency and accuracy of automated construction progress monitoring. The proposed method will address two shortcomings of the previous studies, including the large number of captured images required and the incompleteness and inaccuracy of generated as-built models.

Using the proposed method, the number of required images is minimized in two stages. In the first stage, the manual photogrammetric network design is used to decrease the number of camera stations considering proper constraints. Then the image acquisition is done and the captured images are used to generate 3D points cloud model. In the second stage, a new software for automatic imaging network design is developed and used to cluster and select the optimal images automatically, using the existing dense points cloud model generated before, and the final optimum camera stations are determined. Therefore, the automated progress monitoring can be done by imaging at the selected camera stations to produce periodic progress reports.

The achieved results show that using the proposed manual and automatic imaging network design methods, the number of required images is decreased by 65 and 75 per cent, respectively. Moreover, the accuracy and completeness of points cloud reconstruction is improved and the quantity of performed work is determined with the accuracy, which is close to 100 per cent.

It is believed that the proposed method may present a novel and robust tool for automated progress monitoring using unmanned aerial vehicles and based on photogrammetry and computer vision techniques. Using the proposed method, the number of required images is minimized, and the accuracy and completeness of points cloud reconstruction is improved.

To generate the points cloud reconstruction based on close-range photogrammetry principles, more than hundreds of images must be captured and processed, which is time-consuming and labor-intensive. There has been no previous study to reduce the large number of required captured images. Moreover, lack of images in some areas leads to an incomplete or inaccurate model. This research resolves the mentioned shortcomings.

Investigate the use of two imaging‐based methods – coded pattern projection and laser‐based triangulation – to generate 3D models as input to a rapid prototyping pipeline.

Discusses structured lighting technologies as suitable imaging‐based methods. Two approaches, coded‐pattern projection and laser‐based triangulation, are specifically identified and discussed in detail. Two commercial systems are used to generate experimental results. These systems include the Genex Technologies 3D FaceCam and the Integrated Vision Products Ranger System.

Presents 3D reconstructions of objects from each of the commercial systems.

Provides background in imaging‐based methods for 3D data collection and model generation. A practical limitation is that imaging‐based systems do not currently meet accuracy requirements, but continued improvements in imaging systems will minimize this limitation.

Imaging‐based approaches to 3D model generation offer potential to increase scanning time and reduce scanning complexity.

Introduces imaging‐based concepts to the rapid prototyping pipeline.

In plastic reconstruction surgeries, total auricular reconstruction for microtia is a real challenge. Presently, autogenous costal cartilage and MEDPOR are the chosen materials but none can satisfy the requirements of orthopaedic operation. The purpose of this paper is to examine how to fabricate an ear scaffold with a good shape.

A new approach to form the auricle framework is described. CT scan data of the patient's contralateral “good ear” are used to generate a 3D reconstruction model of the new ear. This model is then imported into rapid prototyping (RP) software to slice. The sliced data drive the fused deposition modeling (FDM) machine to build the ear framework layer by layer. Based on the actual shape of the computer model, FDM technology produces a real feel ear framework to match the size of the opposite good ear.

An artificial human ear was built using FDM technology based on CT images. The auricular framework with polyurethane was a porous structure with good flexibility and biocompatibility. After implanting into the mouse, a real life human ear appeared on the back of the mouse. The experiment indicated that this method provided an efficient way to macrotia reconstruction.

The freeform fabrication technique combined with CT image reconstruction could provide an efficient way to produce a porous structure and solve the framework carving problem in microtia reconstruction.