Multi-View Stereo: A Tutorial: 26 (Foundations and Trends® in Computer Graphics and Vision) - Tapa blanda
Sinopsis
Multi-View Stereo: A Tutorial presents a hands-on view of the field of multi-view stereo with a focus on practical algorithms. Multi-view stereo algorithms are able to construct highly detailed 3D models from images alone. They take a possibly very large set of images and construct a 3D plausible geometry that explains the images under some reasonable assumptions, the most important being scene rigidity. Multi-View Stereo: A Tutorial frames the multiview stereo problem as an image/geometry consistency optimization problem. It describes in detail its main two ingredients: robust implementations of photometric consistency measures, and efficient optimization algorithms. It then presents how these main ingredients are used by some of the most successful algorithms, applied into real applications, and deployed as products in the industry. Finally, it describes more advanced approaches exploiting domain-specific knowledge such as structural priors, and gives an overview of the remaining challenges and future research directions.
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Reseña del editor
Multi-View Stereo: A Tutorial presents a hands-on view of the field of multi-view stereo with a focus on practical algorithms. Multi-view stereo algorithms are able to construct highly detailed 3D models from images alone. They take a possibly very large set of images and construct a 3D plausible geometry that explains the images under some reasonable assumptions, the most important being scene rigidity. Multi-View Stereo: A Tutorial frames the multiview stereo problem as an image/geometry consistency optimization problem. It describes in detail its main two ingredients: robust implementations of photometric consistency measures, and efficient optimization algorithms. It then presents how these main ingredients are used by some of the most successful algorithms, applied into real applications, and deployed as products in the industry. Finally, it describes more advanced approaches exploiting domain-specific knowledge such as structural priors, and gives an overview of the remaining challenges and future research directions.
Reseña del editor
Multi-view stereo algorithms are able to construct highly detailed 3D models from images alone. The applications range from 3D maps to entertainment, computational photography or cultural heritage archival. Multi-view stereo takes a possibly very large set of images and constructs a 3D plausible geometry that explains the images under some reasonable assumptions, the most important being scene rigidity. This book frames the multi-view stereo problem as an image/geometry consistency optimization problem. It describes in detail its main two ingredients: robust implementations of photometric consistency measures and efficient optimization algorithms. It also presents some of the most successful state of-the- art algorithms, real applications and deployed products in industry, more advanced approaches exploiting domain knowledge such as structural priors, and an overview of remaining challenges and future research directions.
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