A Homographic Framework for the Fusion of Multi-View Silhouettes

Abstract

This paper presents a purely image-based approach to fusing foreground silhouette information from multiple arbitrary views. Our approach does not require 3D constructs like camera calibration to carve out 3D voxels or project visual cones in 3D space. Using planar homographies and foreground likelihood information from a set of arbitrary views, we show that visual hull intersection can be performed in the image plane without requiring to go in 3D space. This process delivers a 2D grid of object occupancy likelihoods representing a cross-sectional slice of the object. Subsequent slices of the object are obtained by extending the process to planes parallel to a reference plane in a direction along the body of the object. We show that homographies of these new planes between views can be computed in the framework of plane to plane homologies using the homography induced by a reference plane and the vanishing point of the reference direction. Occupancy grids are stacked on top of each other, creating a three dimensional data structure that encapsulates the object shape and location. Object structure is finally segmented out by minimizing an energy functional over the surface of the object in a level sets formulation. We show the application of our method on complicated object shapes as well as cluttered environments containing multiple objects.