Complete 3D Model Research Articles

Performance comparison analysis of 3D reconstruction modeling software in construction site visualization and mapping

Unmanned aerial vehicle (UAV) technology has overcome the limitations of conventional construction management methods using advanced and automated visualization and 3D reconstruction modeling techniques. Although the mapping techniques and reconstruction modeling software can generate real-time and high-resolution descriptive textural, physical, and spatial data, they may fail to develop an accurate and complete 3D model of the construction site. To generate a quality 3D reconstruction model, the construction manager must optimize the trade-offs among three major software-selection factors: functionalities, technical capabilities, and the system hardware specifications. These factors directly affect the robust 3D reconstruction model of the construction site and objects. Accordingly, the purpose of this research was to apply nine well-established 3D reconstruction modeling software tools (DroneDeploy, COLMAP, 3DF+Zephyr, Autodesk Recap, LiMapper, PhotoModeler, 3D Survey, AgiSoft Photoscan, and Pix4D Mapper) and compare their performances and reliabilities in generating complete 3D models. The research was conducted in an eco-home building at the University of Technology, Malaysia. A series of regression analyses were conducted to compare the performances of the selected 3D reconstruction modeling software in alignment and registration, distance computing, geometric measurement, and plugin execution. Regression analysis determined that among the software programs, LiMapper had the strongest positive linear correlation with the ground truth model. Furthermore, the correlation analysis showed a statistically significant p-value for all software, except for 3D Survey. In addition, the research found that Autodesk Recap generated the most-robust and highest-quality dense point clouds. DroneDeploy can create an accurate point cloud and triangulation without using many points as required by COLMAP and LiMapper. It was concluded that most of the software is robustly, positively, and linearly correlated with the corresponding ground truth model. In the future, other factors involving software selection should be studied, such as vendor-related, user-related, and automation factors.

HIGH ACCURACY 3D DIGITISATION OF THE GOETHE ELEPHANT SKULL USING HAND-HELD 3D SCANNING SYSTEMS AND STRUCTURE FROM MOTION – A COMPARATIVE CASE STUDY

Abstract. The Goethe Elephant skull is a cultural object of great interest. For the highly accurate 3D digitisation of the object, a hand-held 3D scanning system (Creaform GO!Scan) and Structure-from-Motion (DSLR camera) were used. The aim is a complete spatial reconstruction with a resolution of 0.5 mm and an accuracy level of approximate 0.5 mm. The skull consists of three parts, which have very complex but also very simple surface structures. For both methods the data acquisition and processing is described in detail. In both cases, a complete textured meshed 3D model could be calculated without shadows due to the use of camera-fixed lighting. The 3D models fulfil the desired target resolution and accuracy, verified by independent reference lengths and by the manufacturer's specifications. In addition, the colour values of the texture were calibrated with the help of the ColorChecker Digital SG. A visual and geometric comparison of the two models shows that both methods are very well suited for high-precision 3D object reconstruction on a similar level of accuracy. Furthermore, the advantages and disadvantages of the methods are compared. The main advantage of the applied hand-held scanner is the real-time verification of the model during data acquisition. The established SfM convinces with its flexibility regarding resolution and camera positioning.

Documentación y análisis de un cepo de ancla romano y sus elementos iconográficos y epigráficos sellados

This paper aims to present the documentation and analysis methodology carried out on a lead trap from the ancient period, which belongs to the collection of traps in the Museum of Cádiz (Andalusia, Spain). The anchor stock had some interesting characteristics for this research. On the one hand, from the point of view of conservation and restoration, due to the alterations it presented. On the other hand, from a historical and archaeological point of view, it showed signs of reliefs on its surface hidden under the alteration products. The removal of the different layers of alteration that covered the surface during conservation and restoration treatments revealed an unpublished iconographic and epigraphic programme, as well as possible marks of use and manufacture. The poor state of conservation of the original surface made it impossible to visualise the details as a whole, so we applied photogrammetric methods, and subsequently processed models using various GIS analysis and point cloud processing softwares.Two photogrammetric models (in Agisoft PhotoScan) were made to document the trap in general: one prior to the conservation and restoration process; and a second three-dimensional (3D) model once the surface had been cleaned. The purpose of the second model was to visualise the reliefs programme in general, as well as the different surface details. The first complete 3D model of the object was used to perform a virtual reconstruction of the anchor including the elements that did not preserve, using a 3D modelling program (Blender).Nine areas of the stock surface were selected for the analyses of the various iconographic and epigraphic features, which were documented and processed in Agisoft PhotoScan. The Digital Elevation Model (DEM) and point cloud models were then processed with different analyses tools in Geographic Information System (GIS) (such as QGIS) and point cloud processing software (CloudCompare). Our results document a piece of highly interesting information from its surface consisting of reliefs of four dolphins; at least four rectangular stamps: two of them with possible inscriptions, and an anthropomorphic figure. Thanks to the comparative data, we conclude that the four dolphins were made with the same stamp during the stock manufacturing process. Further, we were able to reconstruct the dolphin stamp, partially preserved in each of the reliefs, by unifying the 3D models, thus revealing the original set. This system of stamping by means of reusable dies is well known in other elements such as amphorae but has not been studied in the specific case of lead traps.In the case of the epigraphic elements, the 3D documentation methodology revealed numerous micro-surface details, not visible under conventional documentation techniques, which could help specialists to interpret these inscriptions. Although they have not been analysed in this research, its documentation has promoted the appreciation of surface details that could refer to the manufacturing processes (moulds and tools) or the traces of use, providing historical information on this object. At the same time, the virtual reconstruction of the anchor has aided the formation of hypotheses on the dimensions and original appearance of the anchor. The different tools used, such as raster analysis using shadow mapping and point cloud alignment, proved to be very effective. They have fulfilled the established objectives and have helped to establish a possible analysis methodology for future lead traps with decorative elements. These types of artefacts recovered from underwater sites are very common in museum collections. In many cases, their state of conservation and the difficulty in handling them due to their size and weight make it difficult to document surface details. In this case, the multidisciplinary work of conservation and 3D documentation allows for high-quality documentation that is easy to access and exchange between researchers. The combined use of photogrammetric techniques with virtual RTI provides a non-invasive method for the object, low cost and easy processing compared to other conventional methods.

Portable solution for high-resolution 3D and color texture on-site digitization of cultural heritage objects

A peculiar characteristic of cultural heritage objects is their uniqueness. This results in an enormous importance for their preservation against aging, accidents, destruction etc. Although not replacing physical preservation, one way is the digitization of the objects in their current state by modern scanning technologies. This research describes a new method to combine 3D shape and color texture data acquired without contact to achieve high-resolution 3D representations. The method was basis of a portable 3D digitization system. The portable character allows its application on-site, which is essential for sensitive and non-transportable objects. A structured-light 3D sensor and a photo camera are used to capture the object from various overlapping perspectives. Then, the 3D shape and photographic data are processed and merged into a complete textured 3D model. Resolution and accuracy of the final model are in the range of 0.1 mm. Beyond preservation, the models can be used to make museum objects digitally available for experts or visitors worldwide e.g. in the form of online databases or virtual museums. A first utilization of the presented technology was realized with historic globes, especially with a Schöner globe dating from 1515 as highlight. The used method can be extended beyond RGB texture acquisition using multi-/hyperspectral sensors leading to an increased information content about the objects.

Damage Identification in Warren Truss Bridges by Two Different Time–Frequency Algorithms

Recently, a number of authors have been focusing on drive-by monitoring methods, exploiting sensors mounted on the vehicle rather than on the bridge to be monitored, with clear advantages in terms of cost and flexibility. This work aims at further exploring the feasibility and effectiveness of novel tools for indirect health monitoring of railway structures, by introducing a higher level of accuracy in damage modelling, achieve more close-to-reality results. A numerical study is carried out by means of a FE 3D model of a short span Warren truss bridge, simulating the dynamic interaction of the bridge/track/train structure. Two kinds of defects are simulated, the first one affecting the connection between the lower chord and the side diagonal member, the second one involving the joint between the cross-girder and the lower chord. Accelerations gathered from the train bogie in different working conditions and for different intensities of the damage level are analyzed through two time-frequency algorithms, namely Continuous Wavelet and Huang-Hilbert transforms, to evaluate their robustness to disturbing factors. Compared to previous studies, a complete 3D model of the rail vehicle, together with a 3D structural scheme of the bridge in place of the 2D equivalent scheme widely adopted in the literature, allow a more detailed and realistic representation of the effects of the bridge damage on the vehicle dynamics. Good numerical results are obtained from both the two algorithms in the case of the time-invariant track profile, whereas the Continuous Wavelet Transform is found to be more robust when a deterioration of track irregularity is simulated.

A three-dimensional thermoregulatory model for predicting human thermophysiological responses in various thermal environments

This study presents a complete virtual three-dimensional (3D) model of human thermophysiological responses by integrating detailed heat dissipation model from human skin to environment through spatially heterogeneous (realistic) clothing into human thermoregulation model by two-way coupling. The model considered various heat and mass transfer mechanisms in air and clothing layers such as conduction, natural convection, forced convection, radiation, and evaporation. The numerical setup of the model was presented and simulated using ANSYS Fluent. The developed model is systematically validated against experimental data obtained from authors of published literatures. To demonstrate the robustness and accuracy of the model, it has been validated for a wide range of ambient temperatures (−10.0 to 45 °C), relative humidity (25–86%), activity levels (0.8–3.5 mets), clothing thermal resistances (0.10–2.95 clo), and evaporative resistances (11.5–800 Pa m2/W) including steady-state and transient exposures. This complete 3D model predicted human thermophysiological responses for a wide range of ambient condition with good accuracy. The average RMSD (root mean square deviation) of predicted core and mean skin temperatures was 0.21 °C (maximum RMSD = 0.33 °C) and 0.56 °C (maximum RMSD = 1.03 °C), compared to average standard deviation in measured data 0.26 °C and 0.58 °C, respectively. The model is also able to predict the local skin temperature with an average RMSD of 0.64 °C. Therefore, this newly developed model can be served as a useful tool in analysing human thermophysiological responses and heat stress for any given thermal environment and clothing setting.

Full-Atom Model of the Agonist LPS-Bound Toll-like Receptor 4 Dimer in a Membrane Environment.

The Toll‐like receptor 4 (TLR4)/myeloid differentiation factor 2 (MD‐2) innate immunity system is a membrane receptor of paramount importance as therapeutic target. Its assembly, upon binding of Gram‐negative bacteria lipopolysaccharide (LPS), and also dependent on the membrane composition, finally triggers the immune response cascade. We have combined ab‐initio calculations, molecular docking, all‐atom molecular dynamics simulations, and thermodynamics calculations to provide the most realistic and complete 3D models of the active full TLR4 complex embedded into a realistic membrane to date. Our studies give functional and structural insights into the transmembrane domain behavior in different membrane environments, the ectodomain bouncing movement, and the dimerization patterns of the intracellular Toll/Interleukin‐1 receptor domain. Our work provides TLR4 models as reasonable 3D structures for the (TLR4/MD‐2/LPS)2 architecture accounting for the active (agonist) state of the TLR4, and pointing to a signal transduction mechanism across cell membrane. These observations unveil relevant molecular aspects involved in the TLR4 innate immune pathways and will promote the discovery of new TLR4 modulators.

EVALUATION OF 3D BUILDING MODEL USING TERRESTRIAL LASER SCANNING AND DRONE PHOTOGRAMMETRY

Abstract. The objective of our study is the evaluation of the 3D modeling of buildings and the extraction of structural elements from point clouds obtained using two acquisition techniques (drone and terrestrial laser scanner), as well as the evaluation of the usefulness of their integration. The drone shooting mission was carried using the DJI Phantom 3 Professional and the Sony EXMOR 1/2.3" CMOS RGB camera. For the TLS scanning mission, 9 scanning stations were performed using the FARO Focus S350 laser scanner.To allow the fusion of the two point clouds obtained from drone imagery and TLS, an alignment step is applied. This step was performed using the Iterative Closest Point algorithm. Segmentation was performed using the adapted RANSAC algorithm on point clouds obtained from the drone mission and the TLS mission as well as on the merged point cloud in order to extract structural elements of the building such as windows, doors and stairs. Analysis of the results emphasizes the importance of TLS and drone in 3D modeling. TLS gave better results than the drone in extracting structural elements. This work confirms the importance of complementarity between these two technologies to produce detailed, complete and precise 3D models.

Automatic branch detection of jujube trees based on 3D reconstruction for dormant pruning using the deep learning-based method

Pruning is a time-consuming and labor-intensive practice for managing of dormant jujube orchards, in which dormant pruning is still mainly dependent on manual operation. Automated pruning using a robotic platform could be a better solution to overcome the skilled labor shortage and increased labor costs. With the development of dwarf and dense planting of jujube trees, the tree architectures are suitable for robotic pruning. This study concentrated on the detection and identification of pruning branches, which was a critical step for automating pruning operations. The method in this study mainly consisted of three steps: first, present a vision system based on two synchronous consumer-level RGB-D cameras to obtain the high-quality 3D point cloud in filed; second, propose the reconstruction pipeline for the desired three-dimensional model (basically a complete 3D model) using only two perspectives; and third, automatically segment the trunks and branches based on deep learning method (SPGNet), and then apply the DBSCAN clustering algorithm for estimating branch counts of jujube trees. For the reconstruction of jujube tree, registration errors II (0°-180°) were greater than errors I (0°-55°), and registration errors I (0°-55°) were less than 1 mm under different light conditions. Experimental results demonstrated that trunks and branches were segmented successfully with class accuracies of 0.93 and 0.84, and another metric intersection-over-union (IoU) was 0.85 and 0.76, respectively; the coefficient of determination (R2) values analyzed between the ground-truth and cluster results were 0.83, 0.88, and 0.89 in sunny, cloudy, and night conditions, respectively. These results showed that the proposed method for detecting branches could be utilized to generate substantial information, such as the diameter length and diameter of the branch, which was critical for the automated dormant pruning of jujube trees in the future orchard field.

A Forward-Collision Warning System for Electric Vehicles: Experimental Validation in Virtual and Real Environment

Driver behaviour and distraction have been identified as the main causes of rear end collisions. However a promptly issued warning can reduce the severity of crashes, if not prevent them completely. This paper proposes a Forward Collision Warning System (FCW) based on information coming from a low cost forward monocular camera for low end electric vehicles. The system resorts to a Convolutional Neural Network (CNN) and does not require the reconstruction of a complete 3D model of the surrounding environment. Moreover a closed-loop simulation platform is proposed, which enables the fast development and testing of the FCW and other Advanced Driver Assistance Systems (ADAS). The system is then deployed on embedded hardware and experimentally validated on a test track.

3D Modeling for Kitchen Scene in a Hospital

This research focused on hospital diet management to explore the design of 3D models for kitchen scenes and the facilities of a hospital. Hospital diet management has standard operating procedures, but most people have never seen the kitchen environment within a hospital. Hence, the ongoing research highlights the foodservice procedure and makes a live-action film to complete 3D modeling and animated scenes within a hospital. This research applied the 3ds Max and other multimedia technologies in the medical and healthcare fields. The presentation of the virtualized scene and facilities is realistic and detailed. This research illustrates that the diet management process can be done quickly by 3D modeling and animation. It can also be applied to healthcare education and train new employees who need to understand the carrier’s details as soon as possible.

The 5th-century AD riverine boat of Santa Maria in Padovetere: 3D reconstruction of its shape and context

The digital survey of a 5th century AD riverine boat, together with direct measurements and drawings, has led to a complete 3D model of the boat, with deformations corrected, hull lines reconstructed and missing parts recreated. The different construction solutions of this boat (sewing, mortise-and-tenon joints, clinker planks) have been represented in a detailed 1:1 scale for improved study and display. The discovery of this boat in a tributary of the Po River has allowed for some considerations about the environment in which the boat was built, and about riverine navigation in the Po Valley in late antiquity.

Multi-sensor point cloud data fusion for precise 3D mapping

Multi-sensor data fusion has recently gained a wide attention within the Geomatics research community, as it helps overcome the limitations of a single sensor and enables a complete 3D model for the structure and a better object classification. This study develops a data fusion algorithm, which optimally combines sensor data from a terrestrial and an unmanned aerial system (UAS) to obtain an improved and a complete 3D mapping model of a structure. Terrestrial laser scanner (TLS) data are collected for the exterior of a building along with the DJI Phantom 4 Pro and terrestrial close-range Sony α7R camera images. A number of ground control points and targets are established throughout the scanned building for the photogrammetric process and scans registration. Different point cloud datasets are generated from the TLS, UAS and the terrestrial Sony camera images. The created point clouds from each individual sensor and the fused point clouds are used in different forms, namely the original, denoised and subsampled point clouds. The denoised point cloud dataset is generated through the application of the statistical outlier remover (SOR) filter on the original point clouds. The relative precision of the 3D models is investigated using the multiscale model-to-model cloud comparison (M3C2) method. The TLS-based 3Dmodel is used as a reference. It is found that the precision of the Sony-based 3D model is higher than the other two models for the original and denoised datasets. The fused Sony/UAS-based model provides a complete 3D model with precision higher than the UAS-based model.

A Method for the Automated Construction of 3D Models of Cities and Neighborhoods from Official Cadaster Data for Solar Analysis

3D city models are a useful tool to analyze the solar potential of neighborhoods and cities. These models are built from buildings footprints and elevation measurements. Footprints are widely available, but elevation datasets remain expensive and time-consuming to acquire. Our hypothesis is that the GIS cadastral data can be used to build a 3D model automatically, so that generating complete cities 3D models can be done in a short time with already available data. We propose a method for the automatic construction of 3D models of cities and neighborhoods from 2D cadastral data and study their usefulness for solar analysis by comparing the results with those from a hand-built model. The results show that the accuracy in evaluating solar access on pedestrian areas and solar potential on rooftops with the automatic method is close to that from the hand-built model with slight differences of 3.4% and 2.2%, respectively. On the other hand, time saving with the automatic models is significant. A neighborhood of 400,000 m2 can be built up in 30 min, 50 times faster than by hand, and an entire city of 967 km2 can be built in 8.5 h.

A new single-view 3D pantograph reconstruction aided by prior CAD model

This paper proposes a novel 3D pantograph reconstruction method for the visualization and inspection based on the single-view scanned data and prior Computer-Aided Design (CAD) model. The proposed method uses the point cloud to reconstruct a scanned surface by the fusion of the point cloud and prior CAD surface. Then, a 3D model is reconstructed by integrating the scanned surface and the CAD model through an edge reconstruction process. Finally, the pantograph is inspected by the deviation analysis. The proposed method is validated by the pantograph data collected in a locomotive workshop with line structured light scanning measurement technology. Compared with the state-of-the-art methods, the proposed method can reconstruct the complete 3D model with high accuracy. Furthermore, the reconstructed 3D model has been successfully applied to the anomaly detection and visualization in the pantograph inspection, which is of great significance for improving the pantograph inspection efficiency and reducing traffic accidents.

Path Planning With Automatic Seam Extraction Over Point Cloud Models for Robotic Arc Welding

This letter presents a point cloud based robotic system for arc welding. Using hand gesture controls, the system scans partial point cloud views of workpiece and reconstructs them into a complete 3D model by a linear iterative closest point algorithm. Then, a bilateral filter is extended to denoise the workpiece model and preserve important geometrical information. To extract the welding seam from the model, a novel intensity-based algorithm is proposed that detects edge points and generates a smooth 6-DOF welding path. The methods are tested on multiple workpieces with different joint types and poses. Experimental results prove the robustness and efficiency of this robotic system on automatic path planning for welding applications.

3D Modeling Design of Multirole Virtual Character Based on Visual Communication in Wireless Sensor Networks

In order to solve the problems of poor design effect and time consumption of traditional virtual character modeling design methods, a three‐dimensional (3D) modeling design method of multirole virtual characters based on visual communication is studied. Firstly, the wireless sensor network is used to locate, scan, and collect the human body structure information and convert the coordinates to bind the 3D skeleton. Secondly, according to different human postures, we switch the linear hybrid skin algorithm, spherical hybrid skin algorithm, and double quaternion hybrid skin algorithm; design the geometric surface; and attach it to the 3D skeleton to generate 3D modeling. Finally, based on the influence of visual communication on human eye observation and psychological feeling, the geometric surface is divided twice, and the virtual character is rendered in the way of display, coating, and splicing to obtain a complete 3D modeling of the virtual character. The results show that the positioning coverage of this method is higher, the rendering effect of the hand and head is better, the design time is significantly shortened, and the maximum time is no more than 35 min.

Scale-Aware Multi-View Reconstruction Using an Active Triple-Camera System.

This paper presents an active wide-baseline triple-camera measurement system designed especially for 3D modeling in general outdoor environments, as well as a novel parallel surface refinement algorithm within the multi-view stereo (MVS) framework. Firstly, the pre-processing module converts the synchronized raw triple images from one single-shot acquisition of our setup to aligned RGB-Depth frames, which are then used for camera pose estimation using iterative closest point (ICP) and RANSAC perspective-n-point (PnP) approaches. Afterwards, an efficient dense reconstruction method, mostly implemented on the GPU in a grid manner, takes the raw depth data as input and optimizes the per-pixel depth values based on the multi-view photographic evidence, surface curvature and depth priors. Through a basic fusion scheme, an accurate and complete 3D model can be obtained from these enhanced depth maps. For a comprehensive test, the proposed MVS implementation is evaluated on benchmark and synthetic datasets, and a real-world reconstruction experiment is also conducted using our measurement system in an outdoor scenario. The results demonstrate that (1) our MVS method achieves very competitive performance in terms of modeling accuracy, surface completeness and noise reduction, given an input coarse geometry; and (2) despite some limitations, our triple-camera setup in combination with the proposed reconstruction routine, can be applied to some practical 3D modeling tasks operated in outdoor environments where conventional stereo or depth senors would normally suffer.

Active Vision and Surface Reconstruction for 3D Plant Shoot Modelling.

Plant phenotyping is the quantitative description of a plant's physiological, biochemical, and anatomical status which can be used in trait selection and helps to provide mechanisms to link underlying genetics with yield. Here, an active vision- based pipeline is presented which aims to contribute to reducing the bottleneck associated with phenotyping of architectural traits. The pipeline provides a fully automated response to photometric data acquisition and the recovery of three-dimensional (3D) models of plants without the dependency of botanical expertise, whilst ensuring a non-intrusive and non-destructive approach. Access to complete and accurate 3D models of plants supports computation of a wide variety of structural measurements. An Active Vision Cell (AVC) consisting of a camera-mounted robot arm plus combined software interface and a novel surface reconstruction algorithm is proposed. This pipeline provides a robust, flexible, and accurate method for automating the 3D reconstruction of plants. The reconstruction algorithm can reduce noise and provides a promising and extendable framework for high throughput phenotyping, improving current state-of-the-art methods. Furthermore, the pipeline can be applied to any plant species or form due to the application of an active vision framework combined with the automatic selection of key parameters for surface reconstruction.

Study and 3D survey of the Roman baths in the archaeological site of Lylibaeum (Marsala, Italy)

Archaeological documentation is a fundamental step for research and conservation planning phases. Nowadays traditional recording is always supported by geomatics technologies which offer important support to the growth of archaeological study. The integration of sensors and methodologies seems to give the best results, in terms of time, costs and accuracy of products. In particular, the combination of Terrestrial Laser Scanner (TLS) and Unmanned Aerial Vehicle (UAV) can help the documentation of complex sites and the production of 3D and 2D products for different purposes. The paper focuses on the integration of TLS and UAV methodologies to record the thermal baths of the Roman Domus in the archaeological Park of Lylibaeum (Marsala, Italy). The combination of range and image data are useful to achieve a complete 3D model and a high-resolution orthophoto of the site, in order to provide accurate and complete documentation for archaeological research and conservative project.