Sketching continues to be a vital part of methods and technologies related to Concept Development, including those analyzed in this paper: "concept design with constraints", "solid from sketch", "sketching on a point cloud" and "geometric modeling of design constraints". Existing methods are analyzed and critical subproblems are identified. New solution methods are proposed for the subjects "solid from sketch" and "sketching on a point cloud".
Estimates suggest that more than 75% of engineering design activity comprises reuse of previous design knowledge to address a new design problem. Reusing design knowledge has great potential to improve product quality, shorten lead time, and reduce cost. However, PLM systems, which address the issue of reuse by searching for keywords in filenames, part numbers or context attached to CAD models, do not provide a robust tool to search reusable knowledge. This paper presents a brief overview of a novel approach to search for 3D models. The system is built on a client-server-database architecture. The client takes in the query input from the user along with his search preferences and passes it to the server. The server converts the shape input into feature vectors and a unique skeletal graph representation. Details of the algorithms to perform these steps are presented here. Principal advantages of our graph representation are: (i) it preserves geometry and topology of the query model, (ii) it is considerably smaller than the B-Rep graph, and (iii) it is insensitive to minor perturbations in shape, but sensitive enough to capture the major features of a shape. The combined distance of feature vectors and skeletal graphs in the database provide an indirect measure of shape similarity between models. Critical database issues such as search system efficiency, semantic gap reduction and the subjectivity of the similarity definition are addressed. This paper reports our initial results in designing, implementing and running the shape search system. q
Reverse engineering, the process of obtaining a geometric CAD model from measurements obtained by scanning an existing physical model, is widely used in numerous applications, such as manufacturing, industrial design and jewellery design and reproduction. For creating editable CAD models meant for manufacturing we identify that it is more appropriate to use feature-based constraint-based representations, since they capture plausible design intent. We propose this type of model representation for reverse engineering 3D point clouds of jewellery objects. In this paper we propose an approach for reverse engineering of jewellery combining skeleton construction, feature and constraint information exploitation to obtain a more robust and accurate CAD model. First we automatically construct the skeleton of the point cloud. Constraints are automatically detected based on the skeleton and then an iterative interactive process is carried out, during which features are fitted to the point cloud according to constraints. A voxel inspired technique is also employed to describe repeated patterns common to various types of traditional jewellery.
This paper presents an approach for a reconfigurable shape search system for 3D engineering models using a client-serverdatabase architecture. The current paper focuses on the server functionality, while a subsequent paper will focus on the database issues. The server takes the shape query as input from the client and converts it into feature vectors and a new skeletal graph representation which we have developed. The algorithms such as voxelization, skeletonization, and skeletal graph extraction for accomplishing these are described in detail. The principal advantages of the skeletal graph representation are that (i) it preserves the geometry and topology of the query model, (ii) it is considerably smaller than the B-Rep graph, and (iii) it is insensitive to minor perturbations in shape, while sensitive enough to capture the major features of a shape. Our representation is also synergistic with the human cognitive representation of shape. The results indicate that the skeletal graph is considerably smaller than the B-Rep graph even for complicated shapes.
This paper introduces database and related techniques for a reconfigurable, intelligent 3D engineering shape search system, which retrieves similar 3D models based on their shape content. Feature vectors, which are numeric “fingerprints” of 3D models, and skeletal graphs, which are the “minimal representations of the shape content” of a 3D model, represent the shape content. The Euclidean distance of the feature vectors, as well as the distance between skeletal graphs, provides indirect measures of shape similarity between the 3D models. Critical database issues regarding 3D shape search systems are discussed: (a) database indexing, (b) semantic gap, (c) subjectivity of similarity, and (d) database clustering. An Rtree based multidimensional index is used to speed up the feature-vector based search operation, while a decision treebased approach is used for efficiently indexing/searching skeletal graphs. Interactions among users and the search system, such as relevance feedback and feature vector reconfiguration, are used to bridge the semantic gap and to customize the system for different users. Database clustering of the R-tree index is compared with that generated by a selforganizing map (SOM). Synthetic databases and real 3D model databases are employed to investigate the efficiency of the multidimensional index and the effectiveness of relevance feedback.
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