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

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Multi-view Multi-object Detection and Tracking,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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Shape from Photographs: A Multi-view Stereo Pipeline,deas matured enough to provide highly accurate results. We present a complete algorithm to reconstruct 3D objects from images using the stereo correspondence cue. The technique can be described as a pipeline of four basic building blocks: camera calibration, image segmentation, photo-consistency est

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Practical 3D Reconstruction Based on Photometric Stereo,ver, 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

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Book 20101st editionound at: http://www.dmi.unict.it/icvssThis edited volume contains a selection of articles covering some of the talks and tutorials held during the first two editions of the school on topics such as Recognition, Registration and Reconstruction. The chapters provide an in-depth overview of these chall

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Sally S. Simpson,David Weisburdhways. For evaluating the robustness of our algorithm, we have assembled a challenging dataset consisting real-world images of eight different sport events, most of them collected from the Internet. Experimental results show that our hierarchical model performs better than existing methods.

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