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Re-combining parts of existing 3D object models is an interesting and efficient technique to create novel shape collections. However, due to the lack of direct parts’ correspondence across different shape families, such data-driven modeling approaches in literature are mostly limited to the synthesis of in-class shapes only. To address the problem, this paper proposes a novel approach to create 3D shapes via re-combination of cross-category object parts from an existing database of different model families. In our approach, a reference shape containing multi-functional constituent parts is pre-specified by users, and its design style is then reused to guide the creation process. To this end, the functional substructures are first extracted for the reference shape. After that, we explore a series of category pairs which are potential replacements for the functional substructures of the reference shape to make interesting variations. We demonstrate our ideas using various examples, and present a user study to evaluate the usability and effectiveness of our technique. [ABSTRACT FROM AUTHOR]

3-D object modeling from single images has many applications in computer graphics and multimedia. Most previous 3-D modeling methods which directly recover 3-D geometry from single images require user interactions during the whole modeling process. In this paper, we propose a semi-automatic 3-D modeling approach to recover accurate 3-D geometry from a single image of a piecewise planar object with less user interaction. Our approach concentrates on these three aspects: (1) requiring rough sketch input only, (2) accurate modeling for a large class of objects, and (3) automatically recovering the invisible part of an object and providing a complete 3-D model. Experimental results on various objects show that the proposed approach provides a good solution to these three problems. [ABSTRACT FROM AUTHOR]

Using 2D contour sketches as input is an attractive solution for easing the creation of 3D models. This paper tackles the problem of creating 3D models of animals from a single, side-view sketch. We use the a priori assumptions of smoothness and structural symmetry of the animal about the sagittal plane to inform the 3D reconstruction. Our contributions include methods for identifying and inferring the contours of shape parts from the input sketch, a method for identifying the hierarchy of these structural parts including the detection of approximate symmetric pairs, and a hierarchical algorithm for positioning and blending these parts into a consistent 3D implicit-surface-based model. We validate this pipeline by showing that a number of plausible animal shapes can be automatically constructed from a single sketch. [ABSTRACT FROM AUTHOR]