Fitting Parameterized Three-Dimensional Models to Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Proceedings of the 25th annual conference on Computer graphics and interactive techniques
A Flexible New Technique for Camera Calibration
IEEE Transactions on Pattern Analysis and Machine Intelligence
Motion Tracking: No Silver Bullet, but a Respectable Arsenal
IEEE Computer Graphics and Applications
Model-Based Object Pose in 25 Lines of Code
ECCV '92 Proceedings of the Second European Conference on Computer Vision
A Flexible Tracking Concept Applied to Medical Scenarios Using an AR Window
ISMAR '02 Proceedings of the 1st International Symposium on Mixed and Augmented Reality
Marker Tracking and HMD Calibration for a Video-Based Augmented Reality Conferencing System
IWAR '99 Proceedings of the 2nd IEEE and ACM International Workshop on Augmented Reality
POSTRACK: A Low Cost Real-Time Motion Tracking System for VR Application
VSMM '01 Proceedings of the Seventh International Conference on Virtual Systems and Multimedia (VSMM'01)
Accuracy in Optical Tracking with Fiducial Markers: An Accuracy Function for ARToolKit
ISMAR '04 Proceedings of the 3rd IEEE/ACM International Symposium on Mixed and Augmented Reality
Robust camera pose estimation using 2d fiducials tracking for real-time augmented reality systems
VRCAI '04 Proceedings of the 2004 ACM SIGGRAPH international conference on Virtual Reality continuum and its applications in industry
High-Performance Wide-Area Optical Tracking: The HiBall Tracking System
Presence: Teleoperators and Virtual Environments
A novel optical tracking algorithm for point-based projective invariant marker patterns
ISVC'07 Proceedings of the 3rd international conference on Advances in visual computing - Volume Part I
EHAWC'07 Proceedings of the 2007 international conference on Ergonomics and health aspects of work with computers
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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 markers in a 2D post-processing using a divide-and-conquer strategy to segment the camera's image space and attempts an iterative geometric 3D reconstruction of position and orientation in camera space. Tracking results are made available to applications through OpenTracker [OpenTracker 2006] framework. To analyse tracking accuracy and precision, we built a generic test-bed and compared PTrack to ARToolKit [Kato and Billinghurst 1999; Kato et al. 2000], one of the most wide-spread low-cost tracking solutions. Results show that our tracking system achieves competitive accuracy levels better than ARToolKit and close to commercial systems, while being highly stable and affordable.