Review and analysis of solutions of the three point perspective pose estimation problem
International Journal of Computer Vision
Linear N-Point Camera Pose Determination
IEEE Transactions on Pattern Analysis and Machine Intelligence
Efficient Linear Solution of Exterior Orientation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Linear Pose Estimation from Points or Lines
IEEE Transactions on Pattern Analysis and Machine Intelligence
Matrix: A Realtime Object Identification and Registration Method for Augmented Reality
APCHI '98 Proceedings of the Third Asian Pacific Computer and Human Interaction
Hybrid Inertial and Vision Tracking for Augmented Reality Registration
VR '99 Proceedings of the IEEE Virtual Reality
Accurate Image Overlay on Video See-Through HMDs Using Vision and Accelerometers
VR '00 Proceedings of the IEEE Virtual Reality 2000 Conference
Fusion of Vision and Gyro Tracking for Robust Augmented Reality Registration
VR '01 Proceedings of the Virtual Reality 2001 Conference (VR'01)
Visual Marker Detection and Decoding in AR Systems: A Comparative Study
ISMAR '02 Proceedings of the 1st International Symposium on Mixed and Augmented Reality
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
An Adaptive Estimator for Registration in Augmented Reality
IWAR '99 Proceedings of the 2nd IEEE and ACM International Workshop on Augmented Reality
A real-time tracker for markerless augmented reality
ISMAR '03 Proceedings of the 2nd IEEE/ACM International Symposium on Mixed and Augmented Reality
Robust Visual Tracking for Non-Instrumented Augmented Reality
ISMAR '03 Proceedings of the 2nd IEEE/ACM International Symposium on Mixed and Augmented Reality
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
A Robust Hybrid Tracking System for Outdoor Augmented Reality
VR '04 Proceedings of the IEEE Virtual Reality 2004
Handling Uncertain Sensor Data in Vision-Based Camera Tracking
ISMAR '04 Proceedings of the 3rd IEEE/ACM International Symposium on Mixed and Augmented Reality
Combining Edge and Texture Information for Real-Time Accurate 3D Camera Tracking
ISMAR '04 Proceedings of the 3rd IEEE/ACM International Symposium on Mixed and Augmented Reality
Scene Modelling, Recognition and Tracking with Invariant Image Features
ISMAR '04 Proceedings of the 3rd IEEE/ACM International Symposium on Mixed and Augmented Reality
A Head Tracking Method Using Bird's-Eye View Camera and Gyroscope
ISMAR '04 Proceedings of the 3rd IEEE/ACM International Symposium on Mixed and Augmented Reality
A Fast Initialization Method for Edge-based Registration Using an Inclination Constraint
ISMAR '07 Proceedings of the 2007 6th IEEE and ACM International Symposium on Mixed and Augmented Reality
Human Machine Interaction
Augmented Reality: Handheld Augmented Reality involving gravity measurements
Computers and Graphics
| Hi-index | 0.00 |
This paper describes a new hybrid vision-based registration method with an inclination sensor. In the method, a camera is tracked by solving linear equations under inclination constraint. Linear operations are faster than the nonlinear optimization process, but the output does not usually satisfy the orthonormality constraint. On the contrary, the proposed method calculates the camera position and azimuth directly, thus the result satisfies the orthonormality constraint. Many hybrid approaches using inertia sensors have been proposed for AR/MR. However, such methods still depend on vision-based methods in initialization processes. On the other hand, the proposed method is totally hybrid in that the inclination measured by the sensor is always incorporated in pose calculation process as well as vision information. The method can be used in initialization process of conventional hybrid methods as well as it can be used as an independent registration method. The proposed method can be applied to not only inside-out-style camera tracking but also outside-in-style object tracking.