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Abstract Image matching is a fundamental task in photogrammetry and computer vision. While effective solutions exist for narrow-baseline viewing conditions, using detectors, e.g., based on differences of Gaussians (DoG) and descriptors such as scale-invariant feature transform (SIFT), it still...
Abstract This article presents a method that removes outliers, reduces noise and fills holes in a point cloud using a learned shape prior. The shape prior is learned from a set of training objects using the Gaussian process latent variable model. All training objects are represented by a signed...
Abstract Accurate pose estimation is key for a large number of real world applications. For example, automated cars require fast, recent, accurate, and highly available pose estimates for robust operation. Multiple redundant and complementary localisation systems are therefore installed on most...
Abstract Stereo endoscopes for minimally invasive surgery are well established in different medical applications. They may reduce the intervention time due to a better visual support of the surgeon by stereoscopic viewing. Due to rather difficult image analysis conditions in surgical...
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