12/24/2023 0 Comments PhotosketcherThe compositing step again is based on user scribbles: from the scribbles we predict the desired part using Gaussian Mixture Models and compute an optimal seam using Graphcut. The search is based on a bag-of-features approach using local descriptors for translation invariant part retrieval. Users sketch the rough shape of a desired image part and we automatically search a large collection of images for images containing that part. Compared to existing approaches for synthesising images from parts of other images, Photosketcher works on the image content exclusively, no keywords or other metadata associated with the images is required. We introduce Photosketcher, an interactive system for progressively synthesizing novel images using only sparse user sketches as the input. Mathias Eitz, Ronald Richter, Kristian Hildebrand, Tamy Boubekeur and Marc Alexa Photosketcher: interactive sketch-based image synthesis IEEE Computer Graphics and Applications 2011 In the resulting comparison, our approach is significantly better than any other system described so far. Moreover, we demonstrate how to optimize the parameters of our, as well as other approaches, based on the gathered sketches. We can show objectively that this transform is better suited than other approaches from the literature developed for similar tasks. We develop a targeted feature transform based on Gabor filters for this system. Based on this observation, we decide to use a bag-of-features approach over computer generated line drawings of the objects. The sketches turn out to be generally quite abstract with large local and global deviations from the original shape. For objective evaluation, we collect a large number of query sketches from human users that are related to an existing data base of objects. We develop a system for 3D object retrieval based on sketched feature lines as input. Mathias Eitz, Ronald Richter, Tamy Boubekeur, Kristian Hildebrand and Marc Alexa Sketch-based Shape Retrieval ACM Transactions on Graphics, Proc. Among others, we show that Variational Shape Approximation can be interpreted in the same framework by constraining the metric tensor based on another norm. We also put our approach in the context of other techniques. The resulting technique has applications in shape approximation, particularly in the case of noisy data, where normals are unreliable. We explicitly cover the case of degenerate covariance and provide an algorithm to minimize the CVT energy. Constraining the metric tensors to have unit determinant leads to the optimal distance metric being the inverse covariance matrix of the data (i.e. Concretely, we define the distance metric implicitly as the minimizer of the CVT energy. We present a new approach to anisotropic CVT, where the local distance metric is learned from the embedding of the shape. SMI 2014Īnisotropic centroidal Voronoi tessellations (CVT) are a useful tool for segmenting surfaces in geometric modeling. Mahalanobis Centroidal Voronoi Tessellations Computers & Graphics, Proc.
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