Shape reconstruction of flexible objects from monocular images for industrial applications

Abstract

In this paper, we will present a novel method for shape reconstruction of flexible objects, such as rubber-tubes, from monocular images. We understand shape as the three-dimensional position of a tube model in world space. Model knowledge that is available through CAD-data is used to infer parameters for an active contour algorithm snake. Unlike traditional image-based snakes, our active contour algorithm optimizes fully three-dimensional tube-models in world space by projecting a 3d representation of itself onto the image plane. Using a novel method to estimate a 3d tangent of a curve by means of differential texture distortion, we exploit information from the monocular image that is not used in traditional edge-based active contour methods. Integrating both model and image information as energy terms into the active contour algorithm the 3d position of the tube is iteratively refined until an optimum shape of the tube is found.