Authors: Yuan Sun; Jie Sun; Yong Tsue Lee
Addresses: Phillip Securities Pte. Ltd., 250 North Bridge Road, Singapore. ' Department of Mechanical Engineering, National University of Singapore, 9 Engineering Drive 1, Block EA, 07–08, 117576, Singapore. ' School of Mechanical and Aerospace Engineering, NanYang Technological University, 50 Nanyang Avenue, 639798, Singapore
Abstract: In automatic reconstruction of 3D objects from single line drawings, existing systems are all single-track, containing one general solution for all drawings. This paper proposes a method in which an input drawing is first classified based on dominant features which exist in the drawing, including symmetry, orthogonality and parallelism. The reconstruction is then performed by experts to deal with each class specifically. Drawing classification is done using the technique of support vector machine classification. A specific set of features are selected to form an optimal regularity set for each class, and used in the formulation of the objective function for effective reconstruction. Experimental results show that the proposed system can improve the reconstruction accuracy and efficiency than that of a single-track general 3D reconstruction system.
Keywords: line drawings; hybrid systems; reconstruction experts; support vector machines; SVM; 3D objects; 3D reconstruction; object reconstruction; symmetry; orthogonality; parallelism; drawing classification; intelligent reconstruction.
International Journal of Computer Applications in Technology, 2012 Vol.45 No.2/3, pp.186 - 195
Available online: 30 Nov 2012 *Full-text access for editors Access for subscribers Purchase this article Comment on this article