Titlebook: Computer Vision; Detection, Recogniti Roberto Cipolla,Sebastiano Battiato,Giovanni Maria Book 20101st edition Springer-Verlag Berlin Heidel

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https://doi.org/10.1007/978-3-031-34370-4rical. In this Chapter we propose to tie the design of local features to their systematic evaluation on a realistic ground-truthed dataset. We propose a novel mathematical characterisation of the co-variance properties of the features which accounts for deviation from the usual idealised image affin

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https://doi.org/10.1007/978-3-031-34370-4 been the successes of efficient graph cut based minimization algorithms in solving many low level vision problems such as image segmentation, object reconstruction, image restoration and disparity estimation. The scale and form of computer vision problems introduce many challenges in energy minimiz

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Globalization and White-Collar Crimereferred to as . in Vision. This chapter describes Conditional Random Fields (CRFs) based discriminative models for incorporating context in a principled manner. Unlike the traditional generative Markov Random Fields (MRFs), CRFs allow the use of arbitrarily complex dependencies in the observed data

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Sally S. Simpson,David Weisburd shown that the human visual system is particularly efficient and effective in perceiving high-level meanings in cluttered real-world scenes, such as objects, scene classes, activities and the stories in the images. In this chapter, we discuss a generativemodel approach for classifying complex human

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Globalization and White-Collar Crimen trees that act directly on image pixels, semantic texton forests do not need the expensive computation of filter-bank responses or local descriptors. They are extremely fast to both train and test, especially compared with k-means clustering and nearest-neighbor assignment of feature descriptors.

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Towards a New Regional Policy in Spain,can be represented by object features (such as position, color and silhouette) or by object trajectories in each view. In this Chapter, we classify and survey state-of-the art multi-view tracking algorithms and discuss their applications and algorithmic limitations. Moreover, we present a multi-view

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Resocialising Finance to Exit the Crisisver, in its classic form, Photometric Stereo suffers from two main limitations: Firstly, one needs to obtain images of the 3D scene under multiple different illuminations. As a result the 3D scene needs to remain static during illumination changes, which prohibits the reconstruction of deforming obj