Automated sequence arrangement of 3D point data for surface fitting in reverse engineering

Abstract3D shape similarity seach have been studied for detecting or finding a specified 3D model among 3D CAD model database. We propose to use 3D point data for the search, because it has become easier to obtain 3D point data by photographs. CAD data is converted into 3D point data in advance. Then, using machine learning, we attempt to match those data with the 3D point data acquired in the field. It can be expected that the accuracy of matching is improved by directly handling 3D data. As a preliminary trial, we have tried to clasify 10 kinds of chair models in represented as 3D point data with a machine learning approach. It was suggested that 3D shape matching between 3D point data is possible by our proposed method as the result.

Data exchange between different computer-aided design (CAD) systems is a major problem inhibiting information integration in collaborative engineering environments. Existing CAD data format standards such as STEP and IGES enable geometric data exchange. However, they ignore construction history, features, constraints, and other parametric-based CAD data. As a result, they are inadequate for supporting modification, extension and other important higher-level functionality when accessing an imported CAD model from another CAD system. Achieving such higher-level functionality therefore often requires a time-consuming, error-prone, tedious process of manually recreating the model in the target CAD system. Based on techniques adapted from programming language research, this paper presents an approach to exchanging parametric data between CAD systems using formally-defined conversion semantics. We have demonstrated the utility of our approach by developing a prototype implementation that automates the conversion of 2D sketches between two popular CAD systems: Pro/ENGINEER and SolidWorks. We present examples showing that our approach is able to accurately convert parametric CAD data even in cases where models were constructed using operations from the source CAD system that have no direct counterpart in the target CAD system. Although the case study focuses on 2D interoperability, our approach provides formal foundations for supporting 3D and semantic interoperability between CAD systems.

Automatic Face recognition of people is a challenging problem which has received much attention during the recent years due to its potential multimedia applications in different fields such as 3D videoconference, security applications or video indexing. However, there is no technique that provides a robust solution to all situations and different applications, yet. Face recognition includes a set of challenges like expression variations, occlusions of facial parts, similar identities, resolution of the acquired images, aging of the subjects and many others. Among all these challenges, most of the face recognition techniques have evolved in order to overcome two main problems: illumination and pose variation. Either of these influences can cause serious performance degradation in a 2D face recognition system.Some of the new face recognition strategies tend to overcome both research topics from a 3D perspective. The 3D data points corresponding to the surface of the face may be acquired using different alternatives: A multi camera system (stereoscopy), structured light, range cameras or 3D laser and scanner devices The main advantage of using 3D data is that geometry information does not depend on pose and illumination and therefore the representation of the object does not change with these parameters, making the whole system more robust. However, the main drawback of the majority of 3D face recognition approaches is that they need all the elements of the system to be well calibrated and synchronized to acquire accurate 3D data (texture and depth maps). Moreover, most of them also require the cooperation or collaboration of the subject during a certain period of time. All these requirements can be available during the training stage of many applications. When enrolling a new person in the database, it could be performed off-line, with the help o human interaction and with the cooperation of the subject to be enrolled. On the contrary, the previous conditions are not always available during the test stage. The recognition will be in most of the cases in a semicontrolled or uncontrolled scenario, where the only input of the system will probably consists of a 2D intensity image acquired from a single camera. This leads to a new paradigm where 2D-3D mixed face recognition approaches are used. The idea behind this kind of approaches is that these take profit of the 3D data during the training stage but then they can use either 3D data (when available) or 2D data during the recognition stage. Belonging to this category, some of 2D statistical approaches like Eigenfaces of Fisherfaces have been extended to fit in this new paradigm leading to the Partial Principal Component Analysis (P2CA) approach. This algorithm intends to cope with big pose variations (±90 ∘) by using 180∘ cylindrical texture maps for training the system but then only images acquired from a single, normal camera are used for the recognition. These training images provide pose information from different views (2.5D data). Nevertheless they can also be extended to a complete 3D multimodal system where depth and texture information is used. This chapter is structured as follows: First, a brief overview of the state-of-the-art in face recognition is introduced. The most relevant methods are grouped by multimedia scenarios and concrete applications. Afterwards, novel 2D-3D mixed face recognition approaches will be introduced.KeywordsFace RecognitionLocal Binary PatternMultimedia ApplicationActive Appearance ModelFace SpaceThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

This study examines the potential of computer-aided design (CAD) systems equipped with artificial intelligence (AI) in reducing the workload of dental technicians. We aimed to compare the accuracy and design time of crowns designed using conventional CAD with those designed using AI-equipped CAD. Abutment tooth models of a maxillary right second premolar (FDI classification #15) and a maxillary left first molar (FDI classification #26) were mounted on a dental model to form the master model. Stereolithography data were acquired using an intraoral scanner, and five dental technicians designed one crown each for #15 and #26 using both conventional and AI-equipped CAD systems. With the #15 and #26 crowns, six measuring points were established for comparing the accuracy of the occlusal surfaces and design time of the crowns designed by the two CAD systems. The occlusal surfaces were also compared for the buccal and palatal sides. The accuracy of the occlusal surface was 275.5 ± 116.8 µm and 25.7 ± 13 µm for the conventional CAD and AI-equipped CAD systems, respectively. For the buccal and palatal surface comparisons, the conventional CAD system revealed larger misfits on the palatal side for both #15 and #26, with significant differences observed. No significant differences were noted with the AI-equipped CAD system. The AI-equipped CAD resulted in significantly faster design time for both #15 and #26. The AI-based CAD system significantly reduced design time and enabled the fabrication of uniform crowns regardless of the dental technician's experience and skill.

In recent years, Convolutional Neural Networks (CNNs) have been widely successful for numerous computer vision tasks using 2D color and 3D point data, such as object detection and classification, and 3D pose estimation. Despite these successes, it comes with a price --- CNNs require a vast amount of labeled training data to be successful. Many training datasets are now available, however, they are mostly limited to general objects in the public domain such as people, cars, buildings, fruit, and more. Thus, not all fields have sufficient training data. Even if an adequate number of data samples can be built into a dataset, manually collecting and labeling the training data remains a laborious task. Several approaches to reduce or eradicate the need for training data have been proposed by researchers. The two most popular approaches are training with synthetic data and training on generalized object features. Training with synthetic data refers to the use of computer graphics to generate training data. While this approach has demonstrated success, it comes with its own challenges. In contrast, training a CNN on generalized object features identifies specific local 3D features or control points on objects. Local 3D features and their descriptors have proven in the past to be universally applicable and effective for general object detection, and thus, this method allows for a generalized CNN. A generalized CNN refers to a network architecture that, after initial training, can be specialized for a new task with a minimum amount or no new training data. This dissertation investigates an encoder-decoder architecture and determines the capabilities of it to generalize the CNN architecture for object detection tasks in point cloud data. A CNN is trained to recognize 3D features and demonstrates, without retraining, its successful applicability for point cloud object detection using disparate data. Additionally, the geometric consistency of the descriptors is evaluated to obtain further insight. The results demonstrate that the proposed 3D feature descriptors, and their increased geometric consistency contribute to the increased encoder-decoder architecture performance. In summary, this dissertation contributes a state-of-the-art, generalized, feature descriptor-based CNN architecture that can be transferred to different objects without retraining. Furthermore, it provides insight explaining the increased performance of the CNN compared to the state-of-the-art.

A virtual reality (VR) interface to a feature-based computer-aided design (CAD) system promises to provide a simple interface to a designer of mechanical parts, because it allows intuitive specification of design features such as holes, slots, and protrusions in three-dimensions. Given the current state of a part design, the designer is free to navigate around the part and in part cavities to specify the next feature. This method of feature specification also provides directives to the process-planner regarding the order in which the features may be manufactured. In iterative feature-based design, the existing part cavities represent constraints as to where the designer is allowed to navigate and place the new feature. The CAD system must be able to recognize the part cavities and enforce these constraints. Furthermore, the CAD system must be able to update its knowledge of part cavities when the new feature is added. In this paper, (i) we show how the CAD system can enforce the aforementioned constraints by exploiting the knowledge of part cavities and their adjacencies, and (ii) present efficient methods for updates of the set of part cavities when the designer adds a new feature.

This paper describes computer-aided design for quality — a new, cost-effective methodology for designing high-quality, manufacturable products using computer-aided design (CAD) systems. Traditionally, CAD systems have been used to simulate a producT's characteristics for a given set of values for the design parameters. Thus, designers could study the effects of design choices on a producT's quality before production started. Recent advances in computer hardware technology have given CAD systems increasingly complex and accurate simulation capabilities, permitting simultaneous examination of the effects of changes in many design parameters. But CADQ goes a step further. It provides powerful, statistical, model-fitting methods and optimization techniques that extend the traditional use of CAD systems. Given a set of quality-performance measures, a designer now can interactively pursue a producT's optimal design, while considering manufacturing constraints and characteristics of the customers' environment. Through a case study, we show the application of CADQ to integrated-circuit design.

According to the surface integration of laser technology and computer-aided design and computer-aided manufacturing technology (CAD & CAM), a method that is rebuilt surface of three-dimensional facial reconstruction has been explored. A laser scanning system is used to collect the 3D discrete point data of the facial model, which will be cut up by their characteristics and curvature in order to make a 3D face reconstruction. The maximum reconstructive error is 0.2174mm. Application results indicate that the proposed method is quite satisfactory for facial reconstructive surgery, rehabilitation design and plastic surgery.

The purpose of this report is to demonstrate that modern computer-aided design (CAD), computer-aided manufacturing (CAM), and computer-aided engineering (CAE) systems can be used in the Department of Energy (DOE) Nuclear Weapons Complex (NWC) to design new and remodel old products, fabricate old and new parts, and reproduce legacy data within the inspection uncertainty limits. In this study, two two-dimensional splines are compared with several modern CAD curve-fitting modeling algorithms. The first curve-fitting algorithm is called the Wilson-Fowler Spline (WFS), and the second is called a parametric cubic spline (PCS). Modern CAD systems usually utilize either parametric cubic and/or B-splines.

Surfaces defined by linearly interpolating a two‐dimensional triangulation of a set of scattered data points are frequently used to describe geometry in computer applications. The linear nature of such surfaces simplifies many subsequent operations on the surface such as contouring and volume calculations. However, if the data points defining the surface are sparse, the resulting triangulated surface may be unacceptably rough or irregular. An algorithm is presented for smoothing a triangulated surface by adding extra data points at special locations in the interior of the triangulated region. The incremental addition of the supplemental data points forces the triangulated surface to approximate or converge to a previously specified smooth surface that interpolates the original data points. A unique feature of the algorithm is that any smooth interpolation scheme or surface can be used to smooth the triangulated surface. The algorithm has been implemented on a microcomputer and the results have been satisf...

Explicit surfaces, such as triangulations or wireframe models, have been extensively used to represent the deformable 3D models that are used to fit 3D point and 2D silhouette data. The resulting approaches, however, suffer from the fact that fitting typically involves finding the facets that are closest to the 3D data points or most likely to be silhouette facets. This requires searching, which is slow, and dealing with the non-differentiability of the distance function. By contrast, implicit surface representations allow fitting without search, since one can simply evaluate a differentiable field function at every data point. However, implicit representations are not necessarily the most intuitive ones and users, such as graphics designers, tend to prefer explicit models.

The next stage of modernization of the generalized method proposed by the authors for selecting rational parameters of interference fits based on mathematical modeling using computer-aided design software is completed in work. Numerical calculations of the desired values of the parameters and analysis of their mutual influence on the qualitative selection of joints with an interference fit on a smooth surface are performed using this method. The developed multiparametric complex of mathematical models of suitable standard interference fits is described in detail in the authors’ previous publications. The object of this research is a set of spatial images, which are geometric objects of the specified complex in three-dimensional space. The paper formulates practical recommendations for the effective selection and adoption of rational values for the parameters of the designed fits. At the same time, the geometric images of the studied models are analytically described using the mathematical apparatus of the theory of R-functions based on the author’s computer programs. The numerical-analytical results obtained in this work can be used in the automated design of interference fits.

An evaluation of the relationship between management practices and computer aided design technology

Nowadays, companies are developing more and more collaborative projects, and hence the need to exchange data with many partners, contractors, subcontractors, suppliers, and customers. So, to establish successful collaborations, they must ensure the relevance, coherence, and especially the security of exchanged data. But the Computer-Aided Design (CAD) systems still have gaps that need to be corrected in order to improve the productivity of the design process: they offer few solutions to maintain data consistency within the digital model. Adding to that poor management of changes, the user has to manage the consequences of each change manually. This research explores the role of mates’ assembly, as defined in CAD systems, as a key to maintaining the links between parts in the assembly. In this work, we propose the CAD Assembly Management Model that is based on reference elements, in order to maintain mates between CAD entities when a part is modified by a partner and then reinserted into the assembly CAD, and then propagate changes.

The approaches for designing virtual garments may be categorised as ‘2D to 3D’ and ‘3D to 2D’. The former refers to draping flat digital pattern pieces on a virtual mannequin, and the later indicates the development of clothing design on a realistic body and subsequent flattening into 2D pattern pieces. Several computer-aided design (CAD) systems for garment visualisation in space from flat patterns have already been introduced into the clothing industry. Any industrial application of the pattern flattening technique is yet to be made, due to the non-availability of an appropriate CAD system on the market. This article reviews the historical developments of 3D CAD systems for the clothing industry, and assesses the features of currently available systems on market.