Modeling from Reality / Edition 1

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Overview

This book summarizes the results of the editors' modeling-from-reality (MFR) project, which took place over the last decade. The goal of this project was to develop techniques for modeling real objects and/or environments into geometric and photometric models through computer vision techniques. By developing such techniques, time- consuming modeling process, currently undertaken by human programmers, can be (semi-) automatically performed, and, as a result, one can drastically shorten the developing time of such virtual reality systems, reduce their developing cost, and widen their application areas.
The project was conducted while the authors were at the Computer Science Department of Carnegie Mellon University (CMU) and the Institute of Industrial Science at the University of Tokyo.
Modeling from Reality is suitable for a secondary text in a graduate-level course, and as a reference for researchers and practitioners in industry.

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Product Details

Table of Contents

List of Figures. Preface. Introduction; K. Ikeuchi. Part I: Geometric Modeling. 1. Principal Component Analysis with Missing Data and Its Application to Polyhedral Object Modeling; H. Shum, K. Ikeuchi, R. Reddy. 1. Introduction. 2. Principal Component Analysis with Missing Data. 3. Merging Multiple Views. 4. Surface Patch Tracking. 5. Spatial Connectivity. 6. Experiments. 7. Concluding Remarks.2. Building 3-D Models from Unregistered Range Images; K. Higuchi, M. Hebert, K. Ikeuchi 1. Introduction. 2. Spherical Attribute Images. 3. Registering Multiple Views. 4. Building a Complete Model. 5. Conclusion. 3. Consensus Surfaces for Modeling 3DObjects from Multiple Range Images; M.D. Wheeler, Y. Sato, K. Ikeuchi. 1. Introduction. 2. Approach. 3. Data Merging. 4. Experimental Results. 5. Conclusion. Part II: Photometric Modeling. 4. Object Shape and Reflectance Modeling from Observation; Y. Sato, M.D. Wheeler, K. Ikeuchi. 1. Introduction. 2. Image Acquisition System. 3. Surface Shape Modeling. 4. Surface Reflectance Modeling. 5. Image Synthesis. 6. Conclusion. 5. Eigen-Texture Method : Appearance Compression based on 3D Model; K. Nishino, Y. Sato, K. Ikeuchi.1. Introduction.2. Eigen-Texture Method.3. Implementation. 4. Integrating into real scene. 5. Conclusions. Part III: Environmental Modeling. 6. Acquiring a Radiance Distribution to Superimpose Virtual Objects onto a Real Scene; I. Sato, Y. Sato, K. Ikeuchi. 1. Introduction. 2. Consistency of Geometry. 3. Consistency of Illumination. 4. Superimposing Virtual Objects onto a Real Scene. 5. Experimental Results. 6. Conclusions. 7. Illumination Distribution from Shadows; I. Sato, Y. Sato, K. Ikeuchi. 1. Introduction. 2. Formula for RelatingIllumination Radiance with Image Irradiance. 3. Estimation of Illumination Distribution Using Image Irradiance. 4. Experimental Results. 5. Conclusions. Part IV: Epilogue: MFR to Digitized Great Buddha. 8. The Great Buddha Project: Modeling Cultural Heritage through Observation; D. Miyazaki, T. Oishi, T. Nishikawa, R. Sagawa, K. Nishino, T. Tomomatsu, Y. Takase, K. Ikeuchi. 1. Introduction. 2. Modeling from Reality. 3. Modeling the Great Buddha of Kamakura. References. Index.

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