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
Proceedings of the 16th ACM Symposium on Virtual Reality Software and Technology
Case-based object recognition for airborne fungi recognition
Artificial Intelligence in Medicine
Facet detection and visualizing local structure in graphs
GVE '07 Proceedings of the IASTED International Conference on Graphics and Visualization in Engineering
A comparison of viewing geometries for augmented reality
SCIA'03 Proceedings of the 13th Scandinavian conference on Image analysis
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In augmented reality applications, tracking and registration of both cameras and objects is required because, to combine real and rendered scenes, we must project synthetic models at the right location in real images. Although much work has been done to track objects of interest, initialization of theses trackers often remains manual. Our work aims at automating this step by integrating object recognition and tracking into an AR system. Our emphasis is on the initialization phase of the tracking. We address all the three major aspects of the problem of model-to-image registration: feature detection, correspondence and pose estimation. We havedeveloped a novel approach based on facet detection that greatly reduces the number of possible feature correspondences making it possible to directly compute the transformation which best maps 3-D object to the image plane. We will argue that this approach offers a one-fold speed-up over existing methods. Results of our AR system which integrates initialization and tracking are shown. Our method takes about 5 seconds on our example images.