Image-Based Modeling [electronic resource] /by Long Quan.
by Quan, Long [author.]; SpringerLink (Online service).
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Item type | Current location | Call number | Status | Date due | Barcode |
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TA1637-1638 (Browse shelf) | Available | ||||
TK7882.P3 (Browse shelf) | Available | ||||
Long Loan | MAIN LIBRARY | T385 (Browse shelf) | Available |
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QH359-425 The Evolution of Exudativory in Primates | JA1-92 Responding to a Resurgent Russia | RB155-155.8 Hox Genes | TA1637-1638 Image-Based Modeling | JA1-92 Latinos and the Economy | QC310.15-319 Thermodynamics of Crystalline States | QH324.2-324.25 Patient-Specific Modeling of the Cardiovascular System |
Geometry: fundamentals of multi-view geometry -- Geometry prerequisite -- Multi-view geometry -- Computation: from pixels to 3D points -- Feature point -- Structure from Motion -- Modeling: from 3D points to objects -- Surface modeling -- Hair modeling -- Tree modeling -- Façade modeling -- Building modeling.
“This book guides you in the journey of 3D modeling from the theory with elegant mathematics to applications with beautiful 3D model pictures. Written in a simple, straightforward, and concise manner, readers will learn the state of the art of 3D reconstruction and modeling.” —Professor Takeo Kanade, Carnegie Mellon University About this book: The computer vision and graphics communities use different terminologies for the same ideas This books provides a translation, enabling graphics researchers to apply vision concepts, and vice-versa Independence of chapters allows readers to directly jump into a specific chapter of interest Compared to other texts, gives more succinct treatment overall, and focuses primarily on vision geometry Image-Based Modeling is for graduate students, researchers, and engineers working in the areas of computer vision, computer graphics, image processing, robotics, virtual reality, and photogrammetry. About the Author: Long Quan is a Professor of the Department of Computer Science and Engineering at the Hong Kong University of Science and Technology. He received a Ph.D. degree in Computer Science from INRIA, and has been a CNRS researcher at INRIA. Professor Quan is a Fellow of the IEEE Computer Society.
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