Symmetric Piecewise Planar Object Reconstruction from a Single Image

Abstract

Recovering 3D geometry from a single view of an object is an important and challenging problem in computer vi-sion. Previous methods mainly focus on one specific class of objects without large topological changes, such as cars, faces, or human bodies. In this paper, we propose a novel single view reconstruction algorithm for symmetric piece-wise planar objects that are not restricted to some object classes. Symmetry is ubiquitous in manmade and natural objects and provides rich information for 3D reconstruc-tion. Given a single view of a symmetric piecewise planar object, we first find out all the symmetric line pairs. The ge-ometric properties of symmetric objects are used to narrow down the searching space. Then, based on the symmetric lines, a depth map is recovered through a Markov random field. Experimental results show that our algorithm can ef-ficiently recover the 3D shapes of different objects with sig-nificant topological variations. 1.