Titlebook: Machine Learning for Computer Vision; Roberto Cipolla,Sebastiano Battiato,Giovanni Maria Book 2013 Springer-Verlag Berlin Heidelberg 2013

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Scale-Invariant Vote-Based 3D Recognition and Registration from Point Clouds,rmance over the state of the art in both recognition and registration on a (real and) challenging dataset, by comparing our distance with others in a mean shift framework, as well as with the commonly used Hough voting approach.

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Multiple Classifier Boosting and Tree-Structured Classifiers,ree-structured classifier, called Super tree, to further speed up the classification time of a standard boosting classifier. The proposed methods are demonstrated for object detection, tracking and segmentation tasks.

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Throwing Down the Visual Intelligence Gauntlet,mains such as face detection and optical character recognition. However, the problem of producing truly intelligent machines still remains far from being solved. In this chapter, we first describe some of these recent advances, and then review one approach to moving beyond these limited successes –

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Learning Binary Hash Codes for Large-Scale Image Search,ieval, and non-parametric models for object recognition. Recent work shows that ... are a powerful way to index large collections according to their content. The basic idea is to formulate the projections so as to approximately preserve a given similarity function of interest. Having done so, one ca

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Bayesian Painting by Numbers: Flexible Priors for Colour-Invariant Object Recognition,re factorized into intrinsic properties that are useful for subsequent tasks, such as object classification. It was previously shown how images and objects within images could be described as compositions of regions called structural elements or ‘stels’. In this way, transformations of the reflectan