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Fitting evenness is one key characteristic for three-dimensional objects' optimal fit. The weighted Gaussian imaging method is developed for fitting evenness of auto body taillight fitting optimization.

Fitting boundary contours are extracted from scanning data points. Optimal fitting target is represented with gap and flushness between taillight and auto body. By optimizing the fitting position of the projected boundary contours on the Gaussian sphere, the weighted Gaussian imaging method accomplishes optimal requirements of gap and flushness. A scanning system is established, and the fitting contour of the taillight assembly model is extracted to analyse the quality of the fitting process.

The proposed method accomplishes the fitting optimization for taillight fitting with higher efficiency.

The weighted Gaussian imaging method is used to optimize the taillight fitting. The proposed method optimized the fitting objects' 3-D space, while the traditional fitting methods are based on 2-D algorithm. Its time complexity is O(n3), while those of the traditional methods are O(n5). The results of this research will enhance the understanding of the 3-D optimal fitting and help in systematically improving the productivity and the fitting quality in automotive industry.

Majority of the existing direct slicing methods have generated precise slicing contours from different surface representations, they do not carry any interior information. Whereas, heterogeneous solids are highly preferable for designing and manufacturing sophisticated models. To directly slice heterogeneous solids for additive manufacturing (AM), this study aims to present an algorithm using octree-based subdivision and trivariate T-splines.

This paper presents a direct slicing algorithm for heterogeneous solids using T-splines, which can be applied to AM based on the fused deposition modeling (FDM) technology. First, trivariate T-splines are constructed using a harmonic field with the gradient direction aligning with the slicing direction. An octree-based subdivision algorithm is then used to directly generate the sliced layers with heterogeneous materials. For FDM-based AM applications, the heterogeneous materials of each sliced layer are discretized into a finite number of partitions. Finally, boundary contours of each separated partition are extracted and paired according to the rules of CuraEngine to generate the scan path for FDM machines equipped with multi-nozzles.

The experimental results demonstrate that the proposed algorithm is effective and reliable, especially for solid objects with multiple materials, which could maintain the model integrity throughout the process from the original representation to the final product in AM.

Directly slicing heterogeneous solid using trivariate T-splines will be a powerful supplement to current technologies in AM.

The purpose of this paper is to present a new geometric model based on the mathematical morphology paradigm, specialized to provide determinism to the classic morphological operations. The determinism is needed to model dynamic processes that require an order of application, as is the case for designing and manufacturing objects in CAD/CAM environments.

The basic trajectory-based operation is the basis of the proposed morphological specialization. This operation allows the definition of morphological operators that obtain sequentially ordered sets of points from the boundary of the target objects, inexistent determinism in the classical morphological paradigm. From this basic operation, the complete set of morphological operators is redefined, incorporating the concept of boundary and determinism: trajectory-based erosion and dilation, and other morphological filtering operations.

This new morphological framework allows the definition of complex three-dimensional objects, providing arithmetical support to generating machining trajectories, one of the most complex problems currently occurring in CAD/CAM.

The model proposes the integration of the processes of design and manufacture, so that it avoids the problems of accuracy and integrity that present other classic geometric models that divide these processes in two phases. Furthermore, the morphological operative is based on points sets, so the geometric data structures and the operations are intrinsically simple and efficient. Another important value that no excessive computational resources are needed, because only the points in the boundary are processed.

A hybrid formulation is proposed that incorporates finite element substructuring and Galerkin boundary elements in the numerical solution of Poisson's or Laplace's equation with open boundaries. Substructuring the problem can dramatically decreases the size of matrix to be solved. It is shown that the boundary integration that results from application of Green's first theorem to the weighted residual statement can be used to advantage by imposing potential and flux continuity through the contour which separates the interior and exterior regions. In fact, the boundary integration is of exactly the same form as that found in Galerkin boundary elements.

A fine‐grained video content indexing, retrieval, and adaptation requires accurate metadata describing the video structure and semantics to the lowest granularity, i.e. to the object level. The authors address these requirements by proposing semantic video content annotation tool (SVCAT) for structural and high‐level semantic video annotation. SVCAT is a semi‐automatic MPEG‐7 standard compliant annotation tool, which produces metadata according to a new object‐based video content model introduced in this work. Videos are temporally segmented into shots and shots level concepts are detected automatically using ImageNet as background knowledge. These concepts are used as a guide to easily locate and select objects of interest which are then tracked automatically to generate an object level metadata. The integration of shot based concept detection with object localization and tracking drastically alleviates the task of an annotator. The paper aims to discuss these issues.

A systematic keyframes classification into ImageNet categories is used as the basis for automatic concept detection in temporal units. This is then followed by an object tracking algorithm to get exact spatial information about objects.

Experimental results showed that SVCAT is able to provide accurate object level video metadata.

The new contribution in this paper introduces an approach of using ImageNet to get shot level annotations automatically. This approach assists video annotators significantly by minimizing the effort required to locate salient objects in the video.

Path planning is an important part of three-dimensional (3D) printing data processing technology. This study aims to propose a new path planning method based on a discontinuous grid partition algorithm of point cloud for in situ printing.

Three types of parameters (i.e. structural, process and path interruption parameters) were designed to establish the algorithm model with the path error and the computation amount as the dependent variables. The path error (i.e. boundary error and internal error) was further studied and the influence of each parameter on the path point density was analyzed quantitatively. The feasibility of this method was verified by skin in situ printing experiments.

Path point density was positively correlated with Grid_size and negatively related to other parameters. Point_space, Sparsity and Line_space had greater influence on path point density than Indentation and Grid_size. In skin in situ printing experiment, two layers of orthogonal printing path were generated, and the material was printed accurately in the defect, which proved the feasibility of this method.

This study proposed a new path planning method that converted 3D point cloud data to a printing path directly, providing a new path planning solution for in situ printing. The discontinuous grid partition algorithm achieved controllability of the path planning accuracy and computation amount that could be applied to different processes.

The purpose of this paper is to apply rectangular Bézier surface patches directly into the mathematical formula used to solve boundary value problems modeled by Laplace's equation. The mathematical formula, called the parametric integral equation systems (PIES), will be obtained through the analytical modification of the conventional boundary integral equations (BIE), with the boundary mathematically described by rectangular Bézier patches.

The paper presents the methodology of the analytic connection of the rectangular patches with BIE. This methodology is a generalization of the one previously used for 2D problems.

In PIES the paper separates the necessity of performing simultaneous approximation of both boundary shape and the boundary functions, as the boundary geometry has been included in its mathematical formalism. The separation of the boundary geometry from the boundary functions enables to achieve an independent and more effective improvement of the accuracy of both approximations. Boundary functions are approximated by the Chebyshev series, whereas the boundary is approximated by Bézier patches.

The originality of the proposed approach lies in its ability to automatic adapt the PIES formula for modified shape of the boundary modeled by the Bézier patches. This modification does not require any dividing the patch into elements and creates the possibility for effective declaration of boundary geometry in continuous way directly in PIES.

Tool path generation is the key procedure to fabricate multi‐material (MM) assemblies in rapid prototyping (RP) machines. In slicing MM assembly, there will be 2D regions of different materials. The regions need to be filled into 2.5D slabs. In order to complete all regions in a certain slice faster, tool holders should fill the regions simultaneously. In other words, the tool holders will move around in the RP work envelope concurrently. In such case, interference between tool holders may occur. Therefore, collision‐free path plan should be generated. In this paper, a dexel based spatio‐temporal modelling approach is proposed for detecting collision in rapid manufacturing MM assemblies. The approach is based on 2D regions in dexel representation, which needs only simple computation. As a result, tool holders can fill MM regions simultaneously and efficiently.

Gives a bibliographical review of the finite element meshing and remeshing from the theoretical as well as practical points of view. Topics such as adaptive techniques for meshing and remeshing, parallel processing in the finite element modelling, etc. are also included. The bibliography at the end of this paper contains 1,727 references to papers, conference proceedings and theses/dissertations dealing with presented subjects that were published between 1990 and 2001.

The performance of three frequently used level set-based segmentation methods is examined for the purpose of defining features and boundary conditions for image-based Eulerian fluid and solid mechanics models. The focus of the evaluation is to identify an approach that produces the best geometric representation from a computational fluid/solid modeling point of view. In particular, extraction of geometries from a wide variety of imaging modalities and noise intensities, to supply to an immersed boundary approach, is targeted.

Two- and three-dimensional images, acquired from optical, X-ray CT, and ultrasound imaging modalities, are segmented with active contours, k-means, and adaptive clustering methods. Segmentation contours are converted to level sets and smoothed as necessary for use in fluid/solid simulations. Results produced by the three approaches are compared visually and with contrast ratio, signal-to-noise ratio, and contrast-to-noise ratio measures.

While the active contours method possesses built-in smoothing and regularization and produces continuous contours, the clustering methods (k-means and adaptive clustering) produce discrete (pixelated) contours that require smoothing using speckle-reducing anisotropic diffusion (SRAD). Thus, for images with high contrast and low to moderate noise, active contours are generally preferable. However, adaptive clustering is found to be far superior to the other two methods for images possessing high levels of noise and global intensity variations, due to its more sophisticated use of local pixel/voxel intensity statistics.

It is often difficult to know a priori which segmentation will perform best for a given image type, particularly when geometric modeling is the ultimate goal. This work offers insight to the algorithm selection process, as well as outlining a practical framework for generating useful geometric surfaces in an Eulerian setting.