Simultaneous Pose Estimation and Augmentation of Elastic Surfaces from a Moving Monocular Camera

Abstract

We present in this paper an original method to estimate the pose of a monocular camera while simultaneously modeling and capturing the elastic deformation of the object to be augmented. Our method tackles a challenging problem where ambiguities between rigid motion and non-rigid deformation are present. This issue represents a major lock for the establishment of an efficient surgical augmented reality where endoscopic camera moves and organs deform. Using an underlying physical model to estimate the low stressed regions our algorithm separates the rigid body motion from the elastic deformations using polar decomposition of the strain tensor. Following this decomposition, a constrained minimization, that encodes both the optical and the physical constraints, is resolved at each frame. Results on real and simulated data are exposed to show the effectiveness of our approach.