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Multi-Level Bayesian Models for Environment Perception (Hardcover, 1st ed. 2022) Loot Price: R2,959
Discovery Miles 29 590
Multi-Level Bayesian Models for Environment Perception (Hardcover, 1st ed. 2022): Csaba Benedek

Multi-Level Bayesian Models for Environment Perception (Hardcover, 1st ed. 2022)

Csaba Benedek

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Loot Price R2,959 Discovery Miles 29 590 | Repayment Terms: R277 pm x 12*

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This book deals with selected problems of machine perception, using various 2D and 3D imaging sensors. It proposes several new original methods, and also provides a detailed state-of-the-art overview of existing techniques for automated, multi-level interpretation of the observed static or dynamic environment. To ensure a sound theoretical basis of the new models, the surveys and algorithmic developments are performed in well-established Bayesian frameworks. Low level scene understanding functions are formulated as various image segmentation problems, where the advantages of probabilistic inference techniques such as Markov Random Fields (MRF) or Mixed Markov Models are considered. For the object level scene analysis, the book mainly relies on the literature of Marked Point Process (MPP) approaches, which consider strong geometric and prior interaction constraints in object population modeling. In particular, key developments are introduced in the spatial hierarchical decomposition of the observed scenarios, and in the temporal extension of complex MRF and MPP models. Apart from utilizing conventional optical sensors, case studies are provided on passive radar (ISAR) and Lidar-based Bayesian environment perception tasks. It is shown, via several experiments, that the proposed contributions embedded into a strict mathematical toolkit can significantly improve the results in real world 2D/3D test images and videos, for applications in video surveillance, smart city monitoring, autonomous driving, remote sensing, and optical industrial inspection.

General

Imprint: Springer Nature Switzerland AG
Country of origin: Switzerland
Release date: April 2022
First published: 2022
Authors: Csaba Benedek
Dimensions: 235 x 155mm (L x W)
Format: Hardcover
Pages: 202
Edition: 1st ed. 2022
ISBN-13: 978-3-03-083653-5
Categories: Books > Science & Mathematics > Mathematics > Probability & statistics
Books > Computing & IT > Computer software packages > Other software packages > Mathematical & statistical software
Books > Computing & IT > Applications of computing > Image processing > General
LSN: 3-03-083653-3
Barcode: 9783030836535

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