Yaakov Bar-Shalom, X. Rong Li, Thiagalingam Kirubarajan Expert coverage of the design and implementation of state estimation algorithms for tracking and navigation
Estimation with Applications to Tracking and Navigation treats the estimation of various quantities from inherently inaccurate remote observations. It explains state estimator design using a balanced combination of linear systems, probability, and statistics.
The authors provide a review of the necessary background mathematical techniques and offer an overview of the basic concepts in estimation. They then provide detailed treatments of all the major issues in estimation with a focus on applying these techniques to real systems. Other features include:
* Problems that apply theoretical material to real-world applications
* In-depth coverage of the Interacting Multiple Model (IMM) estimator
* Companion DynaEst(TM) software for MATLAB(TM) implementation of Kalman filters and IMM estimators
* Design guidelines for tracking filters
Suitable for graduate engineering students and engineers working in remote sensors and tracking, Estimation with Applications to Tracking and Navigation provides expert coverage of this important area.

David A. Forsyth, Jean Ponce The accessible presentation of this book gives both a general view of the entire computer vision enterprise and also offers sufficient detail to be able to build useful applications. Users learn techniques that have proven to be useful by first-hand experience and a wide range of mathematical methods. A CD-ROM with every copy of the text contains source code for programming practice, color images, and illustrative movies. Comprehensive and up-to-date, this book includes essential topics that either reflect practical significance or are of theoretical importance. Topics are discussed in substantial and increasing depth. Application surveys describe numerous important application areas such as image based rendering and digital libraries. Many important algorithms broken down and illustrated in pseudo code. Appropriate for use by engineers as a comprehensive reference to the computer vision enterprise.

Jean Gallier As an introduction to fundamental geometric concepts and tools needed for solving problems of a geometric nature using a computer, this book attempts to fill the gap between standard geometry books, which are primarily theoretical, and applied books on computer graphics, computer vision, or robotics, which sometimes do not cover the underlying geometric concepts in detail. Gallier offers an introduction to affine geometry, projective geometry, Euclidean geometry, basics of differential geometry and Lie groups, and a glimpse of computational geometry (convex sets, Voronoi diagrams, and Delaunay triangulations) and explores many of the practical applications of geometry. Some of these applications include computer vision (camera calibration) efficient communication, error-correcting codes, cryptography, motion interpolation, and robot kinematics. This comprehensive text with extensive exercises covers most of the geometric background needed for conducting research in computer graphics, geometric modeling, computer vision, and robotics and as such will be of interest to a wide audience including computer scientists, mathematicians, and engineers.

Richard Hartley, Andrew Zisserman A basic problem in computer vision is to understand the structure of a real world scene. This book covers relevant geometric principles and how to represent objects algebraically so they can be computed and applied. Recent major developments in the theory and practice of scene reconstruction are described in detail in a unified framework. Richard Hartley and Andrew Zisserman provide comprehensive background material and explain how to apply the methods and implement the algorithms. First Edition HB (2000): 0-521-62304-9

Dave Shreiner, The Khronos OpenGL ARB Working Group OpenGL is a powerful software interface used to produce high-quality, computer-generated images and interactive applications using 2D and 3D objects, bitmaps, and color images.

 

The OpenGL®Programming Guide, Seventh Edition, provides definitive and comprehensive information on OpenGL and the OpenGL Utility Library. The previous edition covered OpenGL through Version 2.1. This seventh edition of the best-selling “red book” describes the latest features of OpenGL Versions 3.0 and 3.1. You will find clear explanations of OpenGL functionality and many basic computer graphics techniques, such as building and rendering 3D models; interactively viewing objects from different perspective points; and using shading, lighting, and texturing effects for greater realism. In addition, this book provides in-depth coverage of advanced techniques, including texture mapping, antialiasing, fog and atmospheric effects, NURBS, image processing, and more. The text also explores other key topics such as enhancing performance, OpenGL extensions, and cross-platform techniques.

 

This seventh edition has been updated to include the newest features of OpenGL Versions 3.0 and 3.1, including

  Using framebuffer objects for off-screen rendering and texture updatesExamples of the various new buffer object types, including uniform-buffer objects, transform feedback buffers, and vertex array objectsUsing texture arrays to increase performance when using numerous texturesEfficient rendering using primitive restart and conditional renderingDiscussion of OpenGL’s deprecation mechanism and how to verify your programs for future versions of OpenGL

 

This edition continues the discussion of the OpenGL Shading Language (GLSL) and explains the mechanics of using this language to create complex graphics effects and boost the computational power of OpenGL. The OpenGL Technical Library provides tutorial and reference books for OpenGL. The Library enables programmers to gain a practical understanding of OpenGL and shows them how to unlock its full potential. Originally developed by SGI, the Library continues to evolve under the auspices of the Khronos OpenGL ARB Working Group, an industry consortium responsible for guiding the evolution of OpenGL and related technologies.

Richard Szeliski As humans, we perceive the three-dimensional structure of the world around us with apparent ease. However, despite all of the recent advances in computer vision research, the dream of having a computer interpret an image at the same level as a two-year old remains elusive. Why is computer vision such a challenging problem, and what is the current state of the art?

Computer Vision: Algorithms and Applications explores the variety of techniques commonly used to analyze and interpret images. It also describes challenging real-world applications where vision is being successfully used, both for specialized applications such as medical imaging and fun consumer-level tasks such as image editing and stitching, which students can apply to their own personal photos and videos.

More than just a source of "recipes", this text/reference also takes a scientific approach to basic vision problems, formulating physical models of the imaging process before inverting this process to produce the best possible descriptions of a scene. Exercises are presented throughout the book, with a heavy emphasis on testing algorithms.

Suitable for either an undergraduate or a graduate-level course in computer vision, this textbook focuses on basic techniques that work under real-world conditions and encourages students to push their creative boundaries.

Dr. Richard Szeliski has over twenty years’ experience in computer vision research, most notably at Digital Equipment Corporation and Microsoft.

Sebastian Thrun, Wolfram Burgard, Dieter Fox Probabilistic robotics is a new and growing area in robotics, concerned with perception and control in the face of uncertainty. Building on the field of mathematical statistics, probabilistic robotics endows robots with a new level of robustness in real-world situations.

This book introduces the reader to a wealth of techniques and algorithms in the field. All algorithms are based on a single overarching mathematical foundation. Each chapter provides example implementations in pseudo code, detailed mathematical derivations, discussions from a practitioner's perspective, and extensive lists of exercises and class projects. The book's Web site, http://www.probabilistic-robotics.org, has additional material.

The book is relevant for anyone involved in robotic software development and scientific research. It will also be of interest to applied statisticians and engineers dealing with real-world sensor data.