Calculating the 3D-Pose of Rigid-Objects Using Active Appearance Models
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This paper presents two different algorithms for object tracking and pose estimation. Both methods are based on an appearance model technique called Active Appearance Model (AAM). The key idea of the first method is to utilize two instances of the AAM to track landmark points in a stereo pair of images and perform 3D reconstruction of the landmarks followed by 3D pose estimation. The second method, the AAM matching algorithm is an extension of the original AAM that incorporates the full 6 DOF pose parameters as part of the minimization parameters. This extension allows for the estimation of the 3D pose of any object, without any restriction on its geometry. We compare both algorithms with a previously developed algorithm using a geometric-based approach. The results show that the accuracy in pose estimation of our new appearance-based methods is better than using the geometric-based approach. Moreover, since appearance-based methods do not require customized feature extractions, the new features present a more flexible alternative, especially in situations where extracting features is not simple due to cluttered background, complex and irregular features, etc.
Proceedings of the 2004 IEEE International Conference on Robotics and Automation, pp. 5147-5152, May 2004, New Orleans, LA, USA.