Photogrammetric Computer Vision: Statistics, Geometry, Orientation and Reconstruction

This book is about how to measure things in space. It is an introduction to estimation theory – Bayesian estimation, variance components, and sequential estimation. There are many chapters in this book about camera calibration and geometry reconstruction based on geometric image features.

The authors have backgrounds in geodesy and computer vision. This textbook offers a statistical view of the geometry of multiple view analysis, which is needed for camera calibration and orientation or geometric scene reconstruction based on geometric image features.

Book Summary

Photogrammetric Computer Vision: Statistics, Geometry, Orientation and Reconstruction
Photogrammetric Computer Vision: Statistics, Geometry, Orientation and Reconstruction (image credits Amazon)

Additional Information

  • Language ‏ : ‎ English
  • Hardcover ‏ : ‎ 833 pages
  • ISBN-10 ‏ : ‎ 3319115499
  • ISBN-13 ‏ : ‎ 978-3319115498
  • Item Weight ‏ : ‎ 6.94 pounds
  • Dimensions ‏ : ‎ 8.48 x 1.89 x 11.31 inches

Relevant Categories

  • GIS Programming
  • Remote Sensing & GIS
  • Geographic Information Systems

Detailed Review

This book is very well organized and has been divided into the following three parts.

1. Statistics and Estimation

In this part, the authors have not only written a comprehensive discussion but also given a detailed review of Bayesian estimation and variance components. They have also included examples for sequential estimation of parameters based on Estimation theory.

In short, this book section discusses how to measure things in space. The authors have backgrounds in geometry and computer vision and their discussion is very well justified. This textbook provides a statistical view of the geometry of multiple view analysis which is needed for camera calibration and orientation or geometric scene reconstruction. There are many chapters in this section about Statistics and Estimation theory with reference to Photogrammetry. One review found that “If you want to learn more about the relationship between estimation theory and computer vision, this book is an excellent choice.”

2. Geometry

This textbook has a lot of information on Geometrical objects. The authors have written detailed discussions on points, lines, and planes. They also discuss the homogeneous transformation which allows you to transform points, lines, and planes from one system of coordinates to another. It was interesting to see the relevant discussion on using these transformations when using camera calibration software. This information is definitely useful for new students who are starting out in Photogrammetry and Computer vision.

Geometric transformations and operations are the main subjects of this book. Geometric transformations can be viewed as a set of linear equations, which is used to describe how points in space change with some transformation. In geometry, geometric operations are those that take two or more geometrical objects and produce another object from them. The result of a geometric operation may be either an enlargement or reduction of one or more dimensions on the original shape, without changing its boundary lineaments. That’s why authors have emphasized these core concepts and have given a detailed overview of geometrical concepts.

In other words, geometric transformations and operations include changes to size (enlargement/reduction) as well as changes in orientation (rotation). This is indeed a greater source for students who want to learn about Geometrical transformations.

3. Orientation and Reconstruction

This book also talks about concepts of Orientation and 3d Reconstruction. The authors have explained the scene, geometry, objects and other concepts to lay the foundation for 3D reconstruction.

One major topic in this book talks about Bundle adjustment and Surface reconstruction. These are two important topics that people who work with 3D data should know about. Particularly when they’re doing bundle adjustment, it’s essential to take into account all the errors in the surface model before proceeding with any other steps in their processing pipeline.

Conclusion

This textbook offers a statistical view of the geometry of multiple view analysis, which is needed for camera calibration and orientation or geometric scene reconstruction based on geometric image features. With this book as your guide, you’ll be able to measure things in space with confidence and accuracy without having to rely solely on mathematical computations. For anyone looking to make precise measurements from images–whether it’s satellite data or 3D models created by drones–this book will equip you with all the tools necessary to do so.


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Richard Brown
By Richard Brown

Hi, I am Richard Brown. I am a Geoinformatics graduate from the University of Stuttgart(Germany) with interests in 3D Modelling, Laserscaning, LiDAR, Photogrammetry, and Programming. I have been practicing these technologies for the last two decades. I have a rich collection of LiDAR literature/Books and I am sharing my reviews with fellow Surveyors and Scientists. I feel that collective resource is missing on the internet.


lidarbooks.com is a community efforts. Please contact us with your books/literature suggestions, so that we can extend this lidar books list.

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