Factorization methods for structure from motion

Abstract
In this article we present an overview of factorization methods for recovering structure and motion from image sequences. We distinguish these methods from general nonlinear algorithms primarily by their bilinear formulation in motion and shape parameters. The bilinear formulation makes possible powerful and efficient solution techniques including singular value decomposition. We show how factorization methods apply under various affine camera models and under the perspective camera model, and then we review factorization methods for various features including points, lines, directional point features and line segments. An extension to these methods enables them to segment and recover motion and shape for multiple independently moving objects. Finally we illustrate the generality of the factorization methods with two applications outside structure from motion.

This publication has 15 references indexed in Scilit: