Tracking 3D pose of rigid objects using Inverse Compositional Active Appearance Models

Abstract

This paper presents a method for tracking the 3D pose of rigid objects. The proposed method is a 3D extension of the appearance-based approach called Active Appearance Models (AAM). Here, the 3D shape of the object and the geometry of the camera are added as part of the minimizing parameters of the AAM algorithm in order to determine the full 6 degree-of-freedom (DOF) pose of the object. This work is a twofold, major improvement of our previous work: First by applying the inverse compositional algorithm to the image alignment phase; and second, by incorporating the image gradient information into the same image alignment formulation. Both improvements make the method not only more time efficient, but they also increase the tracking accuracy, especially when the object is not rich in texture. Moreover, since our method is appearance-based, it does not require any customized feature extractions, which also translates into a more flexible alternative to situations with cluttered background, complex and irregular features, etc. The proposed method is compared with our previous work and with a previously developed algorithm using a geometric-based approach.