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Affine Region Tracking And Augmentation Using Mser And Adaptive Sift Model Generation, Matthew James Marano
Affine Region Tracking And Augmentation Using Mser And Adaptive Sift Model Generation, Matthew James Marano
Master's Theses
Relatively complex Augmented Reality (AR) algorithms are becoming widely available due to advancements in affordable mobile computer hardware. To take advantage of this a new method is developed for tracking 2D regions without a prior knowledge of an environment and without developing a computationally expensive world model. In the method of this paper, affinely invariant planar regions in a scene are found using the Maximally Stable Extremal Region (MSER) detector. A region is selected by the user to define a search space, and then the Scale Invariant Feature Transform (SIFT) is used to detect affine invariant keypoints in the region. …