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Innovative Geometric Pose Reconstruction for Marker-based Single Camera Tracking by Pedro Santos; Andre Stork; Alexandre Buaes; Joaquim Jorge is a scholarly article available to read on EtoBox.

What is Innovative Geometric Pose Reconstruction for Marker-based Single Camera Tracking about?

Mobile augmented reality applications are in need of tracking systems which can be wearable and do not cause a high processing load, while still offering reasonable performance, robustness and accuracy. The motivation to develop yet another tracking algorithm is two-fold. Most of the existing approaches use classical optimization techniques such as the Gauss-Newton method. However, since those algorithms were developed to address general optimization problems, they do not fully exploit the structure of the pose estimation problem with its geometric constraint targets. Also, mixed reality applications demand that pose estimation be not only accurate but also robust and computationally efficient. Hence there is a need for algorithms that are as accurate as classical algorithms, yet are also globally convergent and fast enough for real-time applications. In this paper we introduce a new iterative geometric method for pose estimation from four co-planar points and we present the current status of PTrack, an infrared marker-based single camera tracking system benefiting from this approach. Our novel pose estimation algorithm identifies possible labels composed of retro-reflective marker

Author

Pedro Santos; Andre Stork; Alexandre Buaes; Joaquim Jorge

Publisher

ACM

Published

2006

Language

EN