Interactive design of 3D models with geometric constraints

1991 ◽  
Vol 7 (5-6) ◽  
pp. 309-325 ◽  
Author(s):  
Maarten J. G. M. van Emmerik
Keyword(s):  
3D Models ◽  
Geometric Constraints ◽  
Interactive Design

GPDOF — A FAST ALGORITHM TO DECOMPOSE UNDER-CONSTRAINED GEOMETRIC CONSTRAINT SYSTEMS: APPLICATION TO 3D MODELING

2006 ◽  
Vol 16 (05n06) ◽  
pp. 479-511 ◽  
Author(s):  
GILLES TROMBETTONI ◽  
MARTA WILCZKOWIAK
Keyword(s):  
Equation System ◽  
3D Models ◽  
General Purpose ◽  
Constrained Systems ◽  
Geometric Constraints ◽  
Geometric Constraint ◽  
Maximum Matching ◽  
Constraint System ◽  
Constraint Systems ◽  
Geometrical Constraints

Our approach exploits a general-purpose decomposition algorithm, called GPDOF, and a dictionary of very efficient solving procedures, called r-methods, based on theorems of geometry. GPDOF decomposes an equation system into a sequence of small subsystems solved by r-methods, and produces a set of input parameters.1. Recursive assembly methods (decomposition-recombination), maximum matching based algorithms, and other famous propagation schema are not well-suited or cannot be easily extended to tackle geometric constraint systems that are under-constrained. In this paper, we show experimentally that, provided that redundant constraints have been removed from the system, GPDOF can quickly decompose large under-constrained systems of geometrical constraints. We have validated our approach by reconstructing, from images, 3D models of buildings using interactively introduced geometrical constraints. Models satisfying the set of linear, bilinear and quadratic geometric constraints are optimized to fit the image information. Our models contain several hundreds of equations. The constraint system is decomposed in a few seconds, and can then be solved in hundredths of seconds.

scholarly journals INLINING 3D RECONSTRUCTION, MULTI-SOURCE TEXTURE MAPPING AND SEMANTIC ANALYSIS USING OBLIQUE AERIAL IMAGERY

2016 ◽  
Vol XLI-B3 ◽  
pp. 605-612
Author(s):  
D. Frommholz ◽  
M. Linkiewicz ◽  
A. M. Poznanska
Keyword(s):  
Semantic Analysis ◽  
Texture Mapping ◽  
Point Clouds ◽  
3D Models ◽  
Geometric Constraints ◽  
Aerial Images ◽  
Surface Model ◽  
Ray Casting ◽  
Real World Data ◽  
Visible Image

This paper proposes an in-line method for the simplified reconstruction of city buildings from nadir and oblique aerial images that at the same time are being used for multi-source texture mapping with minimal resampling. Further, the resulting unrectified texture atlases are analyzed for fac¸ade elements like windows to be reintegrated into the original 3D models. Tests on real-world data of Heligoland/ Germany comprising more than 800 buildings exposed a median positional deviation of 0.31 m at the fac¸ades compared to the cadastral map, a correctness of 67% for the detected windows and good visual quality when being rendered with GPU-based perspective correction. As part of the process building reconstruction takes the oriented input images and transforms them into dense point clouds by semi-global matching (SGM). The point sets undergo local RANSAC-based regression and topology analysis to detect adjacent planar surfaces and determine their semantics. Based on this information the roof, wall and ground surfaces found get intersected and limited in their extension to form a closed 3D building hull. For texture mapping the hull polygons are projected into each possible input bitmap to find suitable color sources regarding the coverage and resolution. Occlusions are detected by ray-casting a full-scale digital surface model (DSM) of the scene and stored in pixel-precise visibility maps. These maps are used to derive overlap statistics and radiometric adjustment coefficients to be applied when the visible image parts for each building polygon are being copied into a compact texture atlas without resampling whenever possible. The atlas bitmap is passed to a commercial object-based image analysis (OBIA) tool running a custom rule set to identify windows on the contained fac¸ade patches. Following multi-resolution segmentation and classification based on brightness and contrast differences potential window objects are evaluated against geometric constraints and conditionally grown, fused and filtered morphologically. The output polygons are vectorized and reintegrated into the previously reconstructed buildings by sparsely ray-tracing their vertices. Finally the enhanced 3D models get stored as textured geometry for visualization and semantically annotated ”LOD-2.5” CityGML objects for GIS applications.

Analytical weight estimation of landing gear designs

2017 ◽  
Vol 231 (12) ◽  
pp. 2214-2227 ◽  
Author(s):  
RC Munjulury ◽  
P Berry ◽  
D Borhani Coca ◽  
A Parés Prat ◽  
P Krus
Keyword(s):  
Analytical Methods ◽  
3D Models ◽  
Landing Gear ◽  
Interactive Design ◽  
Weight Estimation ◽  
Gear Design ◽  
The Past ◽  
And Performance ◽  
Analytical Weight ◽  
Group Weights

Landing gear weight calculations can be carried out using statistical or analytical methods. Statistical methods were used in the past and offered quick group weights. However, they are not capable of computing accurately the weight of landing gears, which have special geometries and performance. In this work, landing gear weight is computed using analytical methods based on parametric 3D models. The procedure established by Kraus and Wille is applied as a baseline so as to create a procedure capable of dealing with landing gear weight calculations. This method is designed to be as flexible as possible, giving the user the freedom to modify many options and parameters and integrate landing gear design into Robust Aircraft Parametric Interactive Design.

On the Right Parameterization of 3D Models - Case Study

2014 ◽  
Vol 657 ◽  
pp. 715-719
Author(s):  
Ionuţ Lambrescu ◽  
Ion Pană
Keyword(s):  
Degrees Of Freedom ◽  
3D Models ◽  
Point Of View ◽  
Geometric Constraints ◽  
Teaching Process ◽  
E Learning ◽  
On Line ◽  
The Right ◽  
Independent Parameters

All students in mechanical engineering courses receive training in using at least one parametric and associative 3D modeler. From the point of view of the logic behind the geometric design, a very important issue is how to parameterize the model, or put in other words, how to achieve the right balance between dimensions, as independent parameters, formulas (linking dimensions) and geometric constraints (parallel, concentric, horizontal etc.). We arrive following this logic to the notion of degrees of freedom of the model, as expressing the number of dimensions still free for a dynamic edit. The papers aim is to provide a case study capable to assist students in understanding how a good model could be built. The case study will be integrated in an on-line course, offered by our university as an expression of its commitment in developing e-learning applications [.The paper proposes a slightly different approach, compared with the ones presented in [2, 3, . While in the mentioned sources a graph approach is considered, our paper proposes a matrix oriented analysis, coupled with a live analysis of the model behavior. The paper also proposes different other models as good examples to be used in the teaching process.

scholarly journals Manufacturability Oriented Model Correction and Build Direction Optimization for Additive Manufacturing

2019 ◽  
Vol 142 (6) ◽  
Author(s):  
Erva Ulu ◽  
Nurcan Gecer Ulu ◽  
Walter Hsiao ◽  
Saigopal Nelaturi
Keyword(s):  
Additive Manufacturing ◽  
3D Printing ◽  
3D Model ◽  
3D Models ◽  
Geometric Constraints ◽  
Feature Size ◽  
Printing Process ◽  
Model Correction ◽  
Process Characteristics ◽  
Orientation Optimization

Abstract We introduce a method to analyze and modify a shape to make it manufacturable for a given additive manufacturing (AM) process. Different AM technologies, process parameters, or materials introduce geometric constraints on what is manufacturable or not. Given an input 3D model and minimum printable feature size dictated by the manufacturing process characteristics and parameters, our algorithm generates a corrected geometry that is printable with the intended AM process. A key issue in model correction for manufacturability is the identification of critical features that are affected by the printing process. To address this challenge, we propose a topology aware approach to construct the allowable space for a print head to traverse during the 3D printing process. Combined with our build orientation optimization algorithm, the amount of modifications performed on the shape is kept at minimum while providing an accurate approximation of the as-manufactured part. We demonstrate our method on a variety of 3D models and validate it by 3D printing the results.

Feature-Based Geometric Modeling Approach to Surface Micromachined MEMS

2004 ◽  
Author(s):  
Feng Gao ◽  
Steve Y. Hong ◽  
David W. Rosen
Keyword(s):  
Geometric Modeling ◽  
Design Methodology ◽  
Design Method ◽  
Geometric Model ◽  
3D Models ◽  
Geometric Design ◽  
Geometric Constraints ◽  
Mems Devices ◽  
Visual Evaluation ◽  
Feature Based

Geometric modeling is an important aspect of MEMS design. It not only creates geometric models for visual evaluation, but also supplies input for device performance analysis. This paper focuses on developing a feature-based geometric design methodology that enables designers to create fabrication-ready 3D models of MEMS devices without concerning the mask layout. Compared with the present geometric design routine, which builds 3D device models through simulating the fabrication process from the photolithography masks, the function-oriented geometric design method allows designers to establish 3D models by using a set of pre-defined volumetric primitives associated with geometric constraints. The fabrication information is derived from the corresponding function-oriented data specified by designers. Hence, designers are released from the down-stream fabrication planning, and can focus on creative design. This research is the application of feature modeling and constraint-based design to the micro world. The workbench of this system is developed on the geometric model kernel ACIS.

Discussion on Modeling Approach of 3-Dimensional Models Based on Web3D

2013 ◽  
Vol 300-301 ◽  
pp. 261-264
Author(s):  
Xiao Ping Yang ◽  
Wei Ping Hu ◽  
Jing Jing Wang
Keyword(s):  
3D Model ◽  
Technology Development ◽  
Texture Mapping ◽  
3D Models ◽  
Interactive Design ◽  
The Internet ◽  
3 Dimensional ◽  
Modeling Methods ◽  
Internet Browser ◽  
On Line

Web3D can be understood as 3D model displaying for the Internet browser. In the regard of Web3D technology, to name a few, modeling of 3D models, texture mapping of 3D models, interactive design will pose influence on the final on-line displaying. The paper discusses feasibility of Web3D technology development from modeling methods for Web3D models.

scholarly journals INLINING 3D RECONSTRUCTION, MULTI-SOURCE TEXTURE MAPPING AND SEMANTIC ANALYSIS USING OBLIQUE AERIAL IMAGERY

2016 ◽  
Vol XLI-B3 ◽  
pp. 605-612 ◽  
Author(s):  
D. Frommholz ◽  
M. Linkiewicz ◽  
A. M. Poznanska
Keyword(s):  
Semantic Analysis ◽  
Texture Mapping ◽  
Point Clouds ◽  
3D Models ◽  
Geometric Constraints ◽  
Aerial Images ◽  
Surface Model ◽  
Ray Casting ◽  
Real World Data ◽  
Visible Image

This paper proposes an in-line method for the simplified reconstruction of city buildings from nadir and oblique aerial images that at the same time are being used for multi-source texture mapping with minimal resampling. Further, the resulting unrectified texture atlases are analyzed for fac¸ade elements like windows to be reintegrated into the original 3D models. Tests on real-world data of Heligoland/ Germany comprising more than 800 buildings exposed a median positional deviation of 0.31 m at the fac¸ades compared to the cadastral map, a correctness of 67% for the detected windows and good visual quality when being rendered with GPU-based perspective correction. As part of the process building reconstruction takes the oriented input images and transforms them into dense point clouds by semi-global matching (SGM). The point sets undergo local RANSAC-based regression and topology analysis to detect adjacent planar surfaces and determine their semantics. Based on this information the roof, wall and ground surfaces found get intersected and limited in their extension to form a closed 3D building hull. For texture mapping the hull polygons are projected into each possible input bitmap to find suitable color sources regarding the coverage and resolution. Occlusions are detected by ray-casting a full-scale digital surface model (DSM) of the scene and stored in pixel-precise visibility maps. These maps are used to derive overlap statistics and radiometric adjustment coefficients to be applied when the visible image parts for each building polygon are being copied into a compact texture atlas without resampling whenever possible. The atlas bitmap is passed to a commercial object-based image analysis (OBIA) tool running a custom rule set to identify windows on the contained fac¸ade patches. Following multi-resolution segmentation and classification based on brightness and contrast differences potential window objects are evaluated against geometric constraints and conditionally grown, fused and filtered morphologically. The output polygons are vectorized and reintegrated into the previously reconstructed buildings by sparsely ray-tracing their vertices. Finally the enhanced 3D models get stored as textured geometry for visualization and semantically annotated ”LOD-2.5” CityGML objects for GIS applications.

scholarly journals Distance-based protein folding powered by deep learning

2019 ◽  
Vol 116 (34) ◽  
pp. 16856-16865 ◽  
Author(s):  
Jinbo Xu
Keyword(s):  
Protein Folding ◽  
Deep Learning ◽  
Family Size ◽  
Experimental Validation ◽  
Distance Matrix ◽  
Data Bank ◽  
3D Models ◽  
Geometric Constraints ◽  
Central Processing ◽  
Direct Coupling Analysis

Direct coupling analysis (DCA) for protein folding has made very good progress, but it is not effective for proteins that lack many sequence homologs, even coupled with time-consuming conformation sampling with fragments. We show that we can accurately predict interresidue distance distribution of a protein by deep learning, even for proteins with ∼60 sequence homologs. Using only the geometric constraints given by the resulting distance matrix we may construct 3D models without involving extensive conformation sampling. Our method successfully folded 21 of the 37 CASP12 hard targets with a median family size of 58 effective sequence homologs within 4 h on a Linux computer of 20 central processing units. In contrast, DCA-predicted contacts cannot be used to fold any of these hard targets in the absence of extensive conformation sampling, and the best CASP12 group folded only 11 of them by integrating DCA-predicted contacts into fragment-based conformation sampling. Rigorous experimental validation in CASP13 shows that our distance-based folding server successfully folded 17 of 32 hard targets (with a median family size of 36 sequence homologs) and obtained 70% precision on the top L/5 long-range predicted contacts. The latest experimental validation in CAMEO shows that our server predicted correct folds for 2 membrane proteins while all of the other servers failed. These results demonstrate that it is now feasible to predict correct fold for many more proteins lack of similar structures in the Protein Data Bank even on a personal computer.

scholarly journals LOW-COST 3D LASER SCANNING IN AIR ORWATER USING SELF-CALIBRATING STRUCTURED LIGHT

2017 ◽  
Vol XLII-2/W3 ◽  
pp. 105-112 ◽  
Author(s):  
M. Bleier ◽  
A. Nüchter
Keyword(s):  
Laser Scanning ◽  
Low Cost ◽  
Structured Light ◽  
3D Models ◽  
Geometric Constraints ◽  
Depth Information ◽  
Scanning System ◽  
Laser Projector ◽  
In Situ Calibration ◽  
Underwater Camera

In-situ calibration of structured light scanners in underwater environments is time-consuming and complicated. This paper presents a self-calibrating line laser scanning system, which enables the creation of dense 3D models with a single fixed camera and a freely moving hand-held cross line laser projector. The proposed approach exploits geometric constraints, such as coplanarities, to recover the depth information and is applicable without any prior knowledge of the position and orientation of the laser projector. By employing an off-the-shelf underwater camera and a waterproof housing with high power line lasers an affordable 3D scanning solution can be built. In experiments the performance of the proposed technique is studied and compared with 3D reconstruction using explicit calibration. We demonstrate that the scanning system can be applied to above-the-water as well as underwater scenes.

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