IEEE Transactions on Pattern Analysis and Machine Intelligence
An analytic solution for the perspective 4-point problem
Computer Vision, Graphics, and Image Processing
Determination of the Attitude of 3D Objects from a Single Perspective View
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fitting Parameterized Three-Dimensional Models to Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Robust methods for estimating pose and a sensitivity analysis
CVGIP: Image Understanding
Model-based object pose in 25 lines of code
International Journal of Computer Vision - Special issue: image understanding research at the University of Maryland
SCAAT: incremental tracking with incomplete information
Proceedings of the 24th annual conference on Computer graphics and interactive techniques
Linear N-Point Camera Pose Determination
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fast and Globally Convergent Pose Estimation from Video Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Efficient Linear Solution of Exterior Orientation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Theory of Reconstruction from Image Motion
Theory of Reconstruction from Image Motion
Calibration-Free Augmented Reality
IEEE Transactions on Visualization and Computer Graphics
Hi-index | 0.00 |
Augmented reality requires the geometric registration of virtual or remote worlds with the visual stimulus of the user. This can be achieved by tracking the head pose of the user with respect to the reference coordinate system of virtual objects. If tracking is achieved with head-mounted cameras, registration is known in computer vision as pose estimation. Augmented reality is by definition a real-time problem, so we are interested only in bounded and short computational time. We propose a new linear algorithm for pose estimation. Our algorithm shows better performance than the linear algorithm of Quan and Lan [14] and is comparable to the non-predicted time iterative approach of Kumar and Hanson [8].