Geometric computation for machine vision
Geometric computation for machine vision
Model-based object pose in 25 lines of code
International Journal of Computer Vision - Special issue: image understanding research at the University of Maryland
Matrix computations (3rd ed.)
Self-Calibration of a Moving Camera from PointCorrespondences and Fundamental Matrices
International Journal of Computer Vision
A Flexible New Technique for Camera Calibration
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multiple view geometry in computer visiond
Multiple view geometry in computer visiond
Recent Advances in Augmented Reality
IEEE Computer Graphics and Applications
Recursive Estimation of Motion, Structure, and Focal Length
IEEE Transactions on Pattern Analysis and Machine Intelligence
Autocalibration from Planar Scenes
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume I - Volume I
A Stratified Approach to Metric Self-Calibration
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
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This paper addresses the problem of the zooming effect of camera on focal length estimation for augmented reality applications. Our proposed method allows us to merge virtual objects properly into a real scene captured with varying focal length. Virtual objects appearing in the augmented scene need to be merged into the real scene taken with different camera pose (related to rotation and translation parameters) and camera zoom (related to focal length parameter). The system will then calculate appropriate transformation using a template of the marker that is already built in the database. Several tests have been done in comparison between current AR toolkit and our system. The simulation results show that our system is able to achieve more accurate alignment without degenerate motion problem.