Development of Multi-Agent-Based Indoor 3D Reconstruction

Large-scale indoor 3D reconstruction with multiple robots faces challenges in core enabling technologies.This work contributes to a framework addressing localization,coordination,and vision processing for multi-agent reconstruction.A system architecture fusing visible light positioning,multi-agent path finding via reinforcement learning,and 360°camera techniques for 3D reconstruction is proposed.Our visible light positioning algorithm leverages existing lighting for centimeter-level localization without additional infrastructure.Meanwhile,a decentralized reinforcement learning approach is developed to solve the multi-agent path finding problem,with communications among agents optimized.Our 3D reconstruction pipeline utilizes equirectangular projection from 360°cameras to facilitate depth-independent reconstruction from posed monocular images using neural networks.Experimental validation demonstrates centimeter-level indoor navigation and 3D scene reconstruction capabilities of our framework.The challenges and limitations stemming from the above enabling technologies are discussed at the end of each corresponding section.In summary,this research advances fundamental techniques for multi-robot indoor 3D modeling,contributing to automated,data-driven applications through coordinated robot navigation,perception,and modeling.

Study upon Modeling and Visualization of 3D Geologic Body Based on Generalized Tri-Prism

According to the characteristics of bore data,a model of 3D geologic body with generalized tri-prism as the primitive modeling element is constructed while the modeling process and key algorithms of modeling are presented here in detail.Using this method,the original bore data go through Delaunay triangulation to generate irregular triangular network on the surface,and then links stratum segments on the adjoining bores in session to form tri-prisms which would be pinched out.Finally stratified 3D geologic body model is built by an iterated search which searches for consecutive layer of the same property.The result shows that this method can effectively simulate stratified stratum modeling.

3D Shape Reconstruction of Lumbar Vertebra From Two X-ray Images and a CT Model

Structure reconstruction of 3 D anatomy from biplanar X-ray images is a challenging topic. Traditionally, the elastic-model-based method was used to reconstruct 3 D shapes by deforming the control points on the elastic mesh. However, the reconstructed shape is not smooth because the limited control points are only distributed on the edge of the elastic mesh.Alternatively, statistical-model-based methods, which include shape-model-based and intensity-model-based methods, are introduced due to their smooth reconstruction. However, both suffer from limitations. With the shape-model-based method, only the boundary profile is considered, leading to the loss of valid intensity information. For the intensity-based-method, the computation speed is slow because it needs to calculate the intensity distribution in each iteration. To address these issues, we propose a new reconstruction method using X-ray images and a specimen’s CT data. Specifically, the CT data provides both the shape mesh and the intensity model of the vertebra. Intensity model is used to generate the deformation field from X-ray images, while the shape model is used to generate the patient specific model by applying the calculated deformation field.Experiments on the public synthetic dataset and clinical dataset show that the average reconstruction errors are 1.1 mm and1.2 mm, separately. The average reconstruction time is 3 minutes.

Human Body Modeling and Posture Simulating Based on 3D Surface Scan Data

This paper presents a new approach for modeling the human body by considering the motion state and the shape of whole body. The body model consists of a skeleton kinematic model and a surface model. The former is used to determine the posture of the body,and the latter is used to generate the body shape according to the given posture. The body surface is reconstructed with multi-segment B-spline surfaces based on the 3D scan data from a real human body.Using only a few joints parameters and the original surface scan data, the various body postures and the shape can be generated easily. The model has a strong potential of being used for ergonomic design,garment design, virtual reality environment, as well as creating human animation, etc.

3D Vector Reconstruction of the Typical Cervical Vertebra from Anatomical Sections of Korean Visible Human at the Laboratory of Clinical and Digital Anatomy of Paris Descartes University

Aim: To carry out a 3D vector reconstruction of the typical cervical vertebra from anatomical sections of the “Korean Visible Human” for educational purposes. Material and Methods: The anatomical subject was a 33-year-old Korean man who died of leukemia. He was 164 cm tall and weighed 55 kg. This man donated his body to science. Her body was frozen and cut into several anatomical sections after an MRI and CT scan. These anatomical sections were made using a special saw called a 0.2 mm thick cryomacrotome. Thus 8100 cuts were obtained. Only the sections numbered 940 to 1200 were used for our study. A segmentation by manual contouring of the different parts of the typical cervical vertebra was made using the software Winsurf version 3.5 on a laptop PC running Windows 7 equipped with a Ram of 8 gigas. Results: Our 3D vector model of the typical cervical vertebra is easily manipulated using the Acrobat 3DPDF interface. Each part of the vertebra accessible in a menu can be displayed, hidden or made transparent, and 3D labels are available as well as educational menus for learning anatomy. Conclusion: This original work constitutes a remarkable educational tool for the anatomical study of the typical cervical vertebra and can also be used as a 3D atlas for simulation purposes for training in therapeutic gestures.

3D Vector Reconstruction of the Muscles of the Ventral Region of the Neck from Anatomical Sections of Korean Visible Human at the Paris Descartes Anatomy Laboratory

Objective: To carry out a 3D vector reconstruction of the muscles of the ventral region of the neck from anatomical sections of the “Korean Visible Human” for educational purposes. Materials and Methods: The anatomical subject was a 33-year-old Korean man who died of leukemia. He was 164 cm tall and weighed 55 kgs. The anatomical sections were made in 2010 after an MRI and a CT scan. A special saw (cryomacrotome) made it possible to make cuts 0.2 mm thick on the frozen body, i.e. 5960 cuts. Sections numbered 1500 to 2000 (or 500 cuts covering the neck) were used for our study. A segmentation by manual contouring of each anatomical element of the anterior neck region was done using Winsurf version 3.5 software on a laptop PC running Windows 7 equipped with an 8 gigabyte RAM. Results: We modeled the sternocleidomastoid muscles, the supra-hyoid muscles, the infra-hyoid muscles and the muscle structures of the anterior neck region, the aero-digestive axis of the anterior neck region and the vasculo-nervous axis of the neck. This model is easily manipulated using the Acrobat 3Dpdf interface. Each item accessible in a menu can be displayed, hidden or made transparent, and 3D labels are available as well as educational menus for learning anatomy. This vector model has been integrated into the Diva3d virtual dissection table, a new educational tool used by universities and medical schools to learn anatomy. This model was also uploaded to the Sketchfab? website and 3D printed using an ENDER? pro 3 printer. Conclusion: This original work constitutes a remarkable educational tool for the anatomical study of the anterior neck region and can also be used as a 3D atlas for simulation purposes for training in therapeutic gestures.

3D Vector Reconstruction of the Neck Skeleton from the Anatomical Sections of Korean Visible Human at the Anatomical Laboratory of Paris Descartes

Aim: To perform a vector 3D reconstruction of the neck skeleton from the anatomical sections of the “Korean Visible Human” for educational purposes. Material and Methods: The anatomical subject was a 33-year-old Korean male who died of leukemia. It measured 164 cm and weighed 55 kgs. The anatomical cuts were made in 2010 after an MRI and a CT scan. A special saw (cryomacrotome) made it possible to make cuts on the frozen body of 0.2 mm thick or 5960 slices. Sections numbered 1500 to 2000 (500 neck sections) were used for this study. Manual contouring segmentation of each anatomical element of the anterior neck area was done using Winsurf software version 3.5 on a PC. Results: Our vector 3D neck model includes the following: cervical vertebrae, hyoid bone, sternum manubrium and clavicles. This vector model has been integrated into the virtual dissection table Diva3d, a new educational tool used by universities and medical schools to learn anatomy. This model was also put online on the Sketchfab website and printed in 3D using an ENDER 3 printer. Conclusion: This original work is a remarkable educational tool for the study of the skeleton of the neck and can also serve as a 3D atlas for simulation purposes for training therapeutic gestures.

Three-Dimensional Model Reconstruction of Nonwovens from Multi-Focus Images

The three-dimensional(3D)model is of great significance to analyze the performance of nonwovens.However,the existing modelling methods could not reconstruct the 3D structure of nonwovens at low cost.A new method based on deep learning was proposed to reconstruct 3D models of nonwovens from multi-focus images.A convolutional neural network was trained to extract clear fibers from sequence images.Image processing algorithms were used to obtain the radius,the central axis,and depth information of fibers from the extraction results.Based on this information,3D models were built in 3D space.Furthermore,self-developed algorithms optimized the central axis and depth of fibers,which made fibers more realistic and continuous.The method with lower cost could reconstruct 3D models of nonwovens conveniently.

Auto-measuring System of 3-Dimensional Human Body

To realize the automation of fashion industry measuring,designing and manufacturing, the auto-measurement of 3D size of human body is of great importance. The auto measurement system of 3D human body based on Charge Coupled Devices (CCD) and infrared sensors is presented in this paper. The system can measure the bare size of human body that excludes the effect of clothing quickly and accurately.

A 3D Model Reconstruction Method Using Slice Images

Abstract：reconstruction method using slice im-ages is proposed. Wanting to extract the outermost contours from slice images, the method of the improved GVF-Snake model with optimized force field and ray method is employed. And then, the 3D model is reconstructed by contour connection using the im-proved shortest diagonal method and judgment function of contour fracture. The results show that the accuracy of reconstruction 3D model is improved.

3D Model Reconstruction Based on Process Information

The traditional strategy of 3D model reconstruction mainly concentrates on orthographic projections or engineering drawings. But there are some shortcomings. Such as, only few kinds of solids can be reconstructed, the high complexity of time and less information about the 3D model. The research is extended and process card is treated as part of the 3D reconstruction. A set of process data is a superset of 2D engineering drawings set. The set comprises process drawings and process steps, and shows a sequencing and asymptotic course that a part is made from roughcast blank to final product. According to these characteristics, the object to be reconstructed is translated from the complicated engineering drawings into a series of much simpler process drawings. With the plentiful process information added for reconstruction, the disturbances such as irrelevant graph, symbol and label, etc. can be avoided. And more, the form change of both neighbor process drawings is so little that the engineering drawings interpretation has no difficulty; in addition, the abnormal solution and multi-solution can be avoided during reconstruction, and the problems of being applicable to more objects is solved ultimately. Therefore, the utility method for 3D reconstruction model will be possible. On the other hand, the feature information in process cards is provided for reconstruction model. Focusing on process cards, the feasibility and requirements of Working Procedure Model reconstruction is analyzed, and the method to apply and implement the Natural Language Understanding into the 3D reconstruction is studied. The method of asymptotic approximation product was proposed, by which a 3D process model can be constructed automatically and intelligently. The process model not only includes the information about parts characters, but also can deliver the information of design, process and engineering to the downstream applications.

Extraction of Feature Points for Non-Uniform Rational B-Splines(NURBS)-Based Modeling of Human Legs

Methods of digital human modeling have been developed and utilized to reflect human shape features.However,most of published works focused on dynamic visualization or fashion design,instead of high-accuracy modeling,which was strongly demanded by medical or rehabilitation scenarios.Prior to a high-accuracy modeling of human legs based on non-uniform rational B-splines(NURBS),the method of extracting the required quasi-grid network of feature points for human legs is presented in this work.Given the 3 D scanned human body,the leg is firstly segmented and put in standardized position.Then re-sampling of the leg is conducted via a set of equidistant cross sections.Through analysis of leg circumferences and circumferential curvature,the characteristic sections of the leg as well as the characteristic points on the sections are then identified according to the human anatomy and shape features.The obtained collection can be arranged to form a grid of data points for knots calculation and high-accuracy shape reconstruction in future work.

Mechanical Validation of Perfect Tibia 3D Model Using Computed Tomography Scan

In this paper, the Von Mises stresses and stiffnesses measured by experiments on a human cadaveric tibia and composite ones compared to those predicted by a FE model based on the same bone. Modeling of exact geometrical tibia including cortical and spongy bone using human bone CT scan images and mechanical validating of obtained model, is the aim of this study .The model produced by the current study supplies a tool for simulating mechanical test conditions on human tibia.

Preoperative 3D reconstruction and fluorescent indocyanine green for laparoscopic duodenum preserving pancreatic head resection:A case report

BACKGROUND Duodenum-preserving pancreatic head resection(DPPHR)is the choice of surgery for benign or low-grade malignant tumors of the pancreatic head.Laparoscopic DPPHR(LDPPHR)procedure can be improved by preoperative 3D model reconstruction and the use of intravenous indocyanine green fluorescent before surgery for real-time navigation with fluorescent display to guide the surgical dissection and prevention of from injury to vessels and biliary tract.CASE SUMMARY Here we report the successful short-and long-term outcomes after one year following LDPPHR for a 60-year lady who had an uneventful recovery and was discharged home one week after the surgery.CONCLUSION There was no bile leakage or pancreatic leakage or delayed gastric emptying.The histopathology report showed multiple cysts in the pancreatic head and localized pancreatic intraepithelial tumor lesions.The resected margin was free of tumor.

Research on 3D Target Pose Tracking and Modeling

This paper tackles pose tracking and model refinement, one of the fundamental work for 3D photogrammetry. The researches belong to the videometrics, an interdisciplinewhich combines computer vision, digital image processing, photogrammetry and optical measurement. Related works are summarized briefly in this paper. This paper studies the problem of pose tracking for target with 3D model. For the target with accurate 3D model, line model based pose tracking methods are proposed for target which is rich in line features. Experimental results indicate that the proposed methods track the target pose accurately. Normal distance iterative reweighted least squares and distance image iterative least squares methods are proposed to process more general targets. This paper adopts bundle adjustment to tackle pose tracking in image sequence for target with inaccurate 3D line model. The proposed method optimizes the model line parameters and the pose parameters simultaneously. The model line orientation, position and mean angle error, mean position error of the pose are 0.3°,3.5 mm and 0.12°,20.1 mm in simulation experiments of satellite pose tracking. Line features are used to track target pose with unknown 3D model through image sequence. The model line parameters and pose parameters are optimized under the framework of SFM. In simulation experiments, the reconstructed line orientation, position error and mean angle error, mean position error of pose are 0.4°,7.5 mm and 0.16°,23.5 mm.

Real-Time Characterization of Crystal Shape and Size Distribution Based on Moving Window and 3D Imaging in a Stirred Tank

Crystal shape distribution, i.e. the multidimensional size distribution of crystals, is of great importance to their down-stream processing such as in filtration as well as to the end-use properties including the dissolution rate and bioavailability for crystalline pharmaceuticals. Engineering crystal shape and shape distribution requires knowledge about the growth behavior of different crystal facets under varied operational conditions e.g. supersaturations. Measurement of the facet growth rates and growth kinetics of static crystals in a crystallizer without stirring has been reported previously. Here attention is given to study on real-time characterization of the 3D facet growth behavior of crystals in a stirred tank where crystals are constantly moving and rotating. The measurement technique is stereo imaging and the crystal shape reconstruction is based on a stereo imaging camera model. By reference to a case study on potash alum crystallization, it is demonstrated that the crystal size and shape distributions (CSSD) of moving and rotating potash alum crystals in the solution can be reconstructed. The moving window approach was used to correlate 3D face growth kinetics with supersaturation (in the range 0.04 - 0.12) given by an ATR FTIR probe. It revealed that {100} is the fastest growing face, leading to a rapid reduction of its area, while the {111} face has the slowest growth rate, reflected in its area continuously getting larger.

3-D MODELLING OF COMPUTER AIDED GARMENT DESIGN

This paper describes a method of the computer aided garment design,and discusses 3-D humanbody,wire frame modelling,approaches of expressing and a shading model of the 3-D garment.

A Survey on Deep Learning-Based 2D Human Pose Estimation Models

In this article,a comprehensive survey of deep learning-based(DLbased)human pose estimation(HPE)that can help researchers in the domain of computer vision is presented.HPE is among the fastest-growing research domains of computer vision and is used in solving several problems for human endeavours.After the detailed introduction,three different human body modes followed by the main stages of HPE and two pipelines of twodimensional(2D)HPE are presented.The details of the four components of HPE are also presented.The keypoints output format of two popular 2D HPE datasets and the most cited DL-based HPE articles from the year of breakthrough are both shown in tabular form.This study intends to highlight the limitations of published reviews and surveys respecting presenting a systematic review of the current DL-based solution to the 2D HPE model.Furthermore,a detailed and meaningful survey that will guide new and existing researchers on DL-based 2D HPE models is achieved.Finally,some future research directions in the field of HPE,such as limited data on disabled persons and multi-training DL-based models,are revealed to encourage researchers and promote the growth of HPE research.

Image processing based three-dimensional model reconstruction for cross-platform numerical simulation

Numerical simulation is the most powerful computational and analysis tool for a large variety of engineering and physical problems.For a complex problem relating to multi-field,multi-process and multi-scale,different computing tools have to be developed so as to solve particular fields at different scales and for different processes.Therefore,the integration of different types of software is inevitable.However,it is difficult to perform the transfer of the meshes and simulated results among software packages because of the lack of shared data formats or encrypted data formats.An image processing based method for three-dimensional model reconstruction for numerical simulation was proposed,which presents a solution to the integration problem by a series of slice or projection images obtained by the post-processing modules of the numerical simulation software.By means of mapping image pixels to meshes of either finite difference or finite element models,the geometry contour can be extracted to export the stereolithography model.The values of results,represented by color,can be deduced and assigned to the meshes.All the models with data can be directly or indirectly integrated into other software as a continued or new numerical simulation.The three-dimensional reconstruction method has been validated in numerical simulation of castings and case studies were provided in this study.

Skeleton-aware implicit function for single-view human reconstruction

The aim is to reconstruct a complete and detailed clothed human from a single-view input.Implicit function is suitable for this task because it represents fine shape details and varied topology.Current methods,however,often suffer from artefacts such as broken or disembodied body parts,missing details,or depth ambiguity due to the ambiguity and complexity of human articulation.The main issue observed by the authors is structureagnostic.To address these problems,the authors fully utilise the skinned multi-person linear(SMPL)model and propose a method using the Skeleton-aware Implicit Function(SIF).To alleviate the broken or disembodied body parts,the proposed skeleton-aware structure prior makes the skeleton awareness into an implicit function,which consists of a bone-guided sampling strategy and a skeleton-relative encoding strategy.To deal with the missing details and depth ambiguity problems,the authors’body-guided pixel-aligned feature exploits the SMPL to enhance 2D normal and depth semantic features,and the proposed feature aggregation uses the extra geometry-aware prior to enabling a more plausible merging with less noisy geometry.Additionally,SIF is also adapted to the RGB-D input,and experimental results show that SIF outperforms the state-of-the-arts methods on challenging datasets from Twindom and Thuman3.0.