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We consider the problem of simultaneously registering several images to a 3D model. We propose a global approach based on mutual information that extends previous methods to incorporate the color, and does not require segmentation or feature extraction . We give a stochastic model for joint optimization of multiple image-to-model a lignment and we propose a(More)
Clustering algorithms are intensively used in the image analysis field in compression, segmentation, recognition and other tasks. In this work we present a new approach in clustering vector datasets by finding a good order in the set, and then applying an optimal segmentation algorithm. The algorithm heuristically prolongs the optimal scalar quantization(More)
A I:mtruct. JIl t.cIl.~ily based l'cgisll'"lioll methods, Rl1 ch lIS the 11IUllll11 ;11 fOl'ltLnt ioH (M Jl, do not cOllllUonly oollsiticr tIn: sputial gcolUcll'ic il1rol" malion nnd the initinl corrCllpondences MC uncertainty. III tllis paper, wc prcscnt Il lIov()1 (lppronch for IIchieving highlY-l\utOlrlntic 2D/30 imngc I'cgislrnliOIl illtcgmtillg the(More)
This thesis considers texture reconstruction for scanned 3D models. Given a geometric model and several photographs of the object, the texture is reconstructed in two steps: firstly, the images are registered (aligned) to the model, and, secondly, the texture is constructed from images. We split the first problem into initial registration, followed by(More)
In the process of digitizing the geometry and appearance of 3D objects, texture registration is a necessary step that solves the 2D–3D mapping between the 2D texture images and the 3D geometric model. For evaluation of texture registration with ground truth, accurate datasets can be obtained with a complex setup consisting of calibrated geometry and texture(More)
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