Discovering Structured Variations Via Template Matching. (5th January 2016)

• Record Type: Journal Article
• Authors: Ceylan, Duygu; Dang, Minh; Mitra, Niloy J.; Neubert, Boris; Pauly, Mark
• Is Part Of: Computer graphics forum. Volume 36:Number 1(2017)
• Page Start: 76
• Page End: 88
• Publication Date: 2016-01-05
• Subjects: shape analysis -- template matching -- I.3.5 [Computer Graphics]: Computational Geometry and Object Modelling; Computer graphics -- Periodicals; 006.605
• DOI: 10.1111/cgf.12788
• Languages: English
• ISSNs: 0167-7055

Abstract

Abstract : Understanding patterns of variation from raw measurement data remains a central goal of shape analysis. Such an understanding reveals which elements are repeated, or how elements can be derived as structured variations from a common base element. We investigate this problem in the context of 3D acquisitions of buildings. Utilizing a set of template models, we discover geometric similarities across a set of building elements. Each template is equipped with a deformation model that defines variations of a base geometry. Abstract: Understanding patterns of variation from raw measurement data remains a central goal of shape analysis. Such an understanding reveals which elements are repeated, or how elements can be derived as structured variations from a common base element. We investigate this problem in the context of 3D acquisitions of buildings. Utilizing a set of template models, we discover geometric similarities across a set of building elements. Each template is equipped with a deformation model that defines variations of a base geometry. Central to our algorithm is a simultaneous template matching and deformation analysis that detects patterns across building elements by extracting similarities in the deformation modes of their matching templates. We demonstrate that such an analysis can successfully detect structured variations even for noisy and incomplete data.