Computer Vision

Title : Computer Vision
Author : Linda Shapiro and George Stockman
Publisher: -
ISBN : -

Overview :

This book is intended as an introduction to computer vision for a broad audience. It provides necessary theory and examples for students and practicioners who will work in fields where significant information must be extracted automatically from images. The book should be a useful resource book for professionals, a text for both undergraduate and beginning graduate courses, and a resource for enrichment of college or even high school projects. Our goals were to provide a basic set of fundamental concepts and algorithms and also discuss some of the exciting evolving application areas. This book is unique in that it contains chapters on image databases and on virutal and augmented reality, two exciting evolving application areas. A final chapter gives a complete view of real world systems that use computer vision.

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Computer Vision A Modern Approach

Title : Computer Vision A Modern Approach
Pub Date : -
Author : Forsyth & Ponce
Publisher: -
ISBN : -

Overview :
Part I - Image Formations
Part II - Image Models
Part III - Early Vision: One Image
Part IV - Early Vision: Multiple views
Part V - Mid-Level Vision
Part VI - High-Level Vision
Part VII - Applications and Topics

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Computer Vision and Applications - A Guide for Students and Practitioners

Title : Computer Vision and Applications - A Guide for Students and Practitioners
Author : Bernd Jähne and Horst Haußecker (Editors)
Publisher: Academic Press
ISBN : 0–12–379777-2

Overview :

This book offers a fresh approach to computer vision. The whole vision process from image formation to measuring, recognition, or reacting is regarded as an integral process. Computer vision is understood as the host of techniques to acquire, process, analyze, and understand complex higher-dimensional data from our environment for scientific and technical exploration.

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Handbook of Computer Vision and Applications- Volume 1: Sensors and Imaging

Ebook Title : Handbook of Computer Vision and Applications- Volume 1: Sensors and Imaging

Author : Bernd Jähne, Horst Hauecker & Peter Geiler (Editors)

Publisher: ACADEMIC PRESS

ISBN : 0–12–379771-3

Overview :

This handbook oers a fresh approach to computer vision. The whole vision process from image formation to measuring, recognition, or reacting is regarded as an integral process. Computer vision is understood as the host of techniques to acquire, process, analyze, and understand complex higher-dimensional data from our environment for scientific and technical exploration.

In this sense the handbook takes into account the interdisciplinary nature of computer vision with its links to virtually all natural sciences and attempts to bridge two important gaps. The first is between modern physical sciences and the many novel techniques to acquire images. The second is between basic research and applications. When a reader with a background in one of the fields related to computer vision feels he has learned something from one of the many other facets of computer vision, the handbook will have fulfilled its purpose.

The handbook comprises three volumes. The first volume, Sensors and Imaging, covers image formation and acquisition. The second volume, Signal Processing and Pattern Recognition, focuses on processing of the spatial and spatiotemporal signal acquired by imaging sensors. The third volume, Systems and Applications, describes how computer vision is integrated into systems and applications.

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Handbook of Computer Vision and Applications - Volume 2: Signal Processing and Pattern Recognition

Ebook Title : Handbook of Computer Vision and Applications - Volume 2: Signal Processing and Pattern Recognition

Author : Bernd Jähne, Horst Hauecker & Peter Geiler (Editors)

Publisher: ACADEMIC PRESS

ISBN : 0–12–379772–1

Overview :

This handbook covers a fresh approach to computer vision. The whole vision process from image formation to measuring, recognition, or reacting is regarded as an integral process. Computer vision is understood as the host of techniques to acquire, process, analyze, and understand complex higher-dimensional data from our environment for scientific and technical exploration.

In this sense the handbook takes into account the interdisciplinary nature of computer vision with its links to virtually all natural sciences and attempts to bridge two important gaps. The first is between modern physical sciences and the many novel techniques to acquire images. The second is between basic research and applications. When a reader with a background in one of the fields related to computer vision feels he has learned something from one of the many other facets of computer vision, the handbook will have fulfilled its purpose.

The handbook comprises three volumes. The first volume, Sensors and Imaging, covers image formation and acquisition. The second volume, Signal Processing and Pattern Recognition, focuses on processing of the spatial and spatiotemporal signal acquired by imaging sensors. The third volume, Systems and Applications, describes how computer vision is integrated into systems and applications.

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Handbook of Computer Vision and Applications - Volume 3: Systems and Applications

E-book Title : Handbook of Computer Vision and Applications - Volume 3: Systems and Applications

Author : Bernd Jähne, Horst Hauecker & Peter Geiler (Editors)

Publisher: ACADEMIC PRESS

ISBN : 0–12–379773-X

Overview :

This handbook covers a fresh approach to computer vision. The whole vision process from image formation to measuring, recognition, or reacting is regarded as an integral process. Computer vision is understood as the host of techniques to acquire, process, analyze, and understand complex higher-dimensional data from our environment for scientific and technical exploration.

In this sense the handbook takes into account the interdisciplinary nature of computer vision with its links to virtually all natural sciences and attempts to bridge two important gaps. The first is between modern physical sciences and the many novel techniques to acquire images. The second is between basic research and applications. When a reader with a background in one of the fields related to computer vision feels he has learned something from one of the many other facets of computer vision, the handbook will have fulfilled its purpose.

The handbook comprises three volumes. The first volume, Sensors and Imaging, covers image formation and acquisition. The second volume, Signal Processing and Pattern Recognition, focuses on processing of the spatial and spatiotemporal signal acquired by imaging sensors. The third volume, Systems and Applications, describes how computer vision is integrated into systems and applications.

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HANDBOOK OF Computer Vision Algorithms in Image Algebra second edition

Title : HANDBOOK OF Computer Vision Algorithms in Image Algebra second edition
Author : Gerhard X. Ritter & Joseph N. Wilson
Publisher: CRC Press
ISBN : 0-8493-0075-4

Overview :

Chapter 1 provides a short introduction to the field of image algebra. Chapters 2–12 are devoted to particular techniques commonly used in computer vision algorithm development, ranging from early processing techniques to such higher level topics as image descriptors and artificial neural networks. Although the chapters on techniques are most naturally studied in succession, they are not tightly interdependent and can be studied according to the reader’s particular interest. In the Appendix we present iac++ computer programs of some of the techniques surveyed in this book. These programs reflect the image algebra pseudocode presented in the chapters and serve as examples of how image algebra pseudocode can be converted into efficient computer programs.

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Image Algebra second edition

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Learning Bayesian Networks

Overview :

Bayesian networks are graphical structures for representing the probabilistic relationships among a large number of variables and doing probabilistic inference with those variables. During the 1980’s, a good deal of related research was done on developing Bayesian networks (belief networks, causal networks, influence diagrams), algorithms for performing inference with them, and applications that used them. However, the work was scattered throughout research articles. My purpose in writing the 1990 text Probabilistic Reasoning in Expert Systems was to unify this research and establish a textbook and reference for the field which has come to be known as ‘Bayesian networks.’ The 1990’s saw the emergence of excellent algorithms for learning Bayesian networks from data. However,by 2000 there still seemed to be no accessible source for ‘learning Bayesian networks.’ Similar to my purpose a decade ago, the goal of this text is to provide such a source.

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Fundamentals of Computer Vision

E-book Title : Fundamentals of Computer Vision
Pub Date : 7 December 1997
Author : Mubarak Shah

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Mining Imperfect Data: Dealing with Contamination and Incomplete Records

Mining Imperfect Data: Dealing with Contamination and Incomplete Records
Ronald K. Pearson | 2005-04-01 00:00:00 | SIAM: Society for Industrial and Applied Mathematics | 305 | Artificial Intelligence
Data mining is concerned with the analysis of databases large enough that various anomalies, including outliers, incomplete data records, and more subtle phenomena such as misalignment errors, are virtually certain to be present. Mining Imperfect Data: Dealing with Contamination and Incomplete Records describes in detail a number of these problems, as well as their sources, their consequences, their detection, and their treatment. Specific strategies for data pretreatment and analytical validation that are broadly applicable are described, making them useful in conjunction with most data mining analysis methods. Examples are presented to illustrate the performance of the pretreatment and validation methods in a variety of situations; these include simulation-based examples in which "correct" results are known unambiguously as well as real data examples that illustrate typical cases met in practice.

Mining Imperfect Data, which deals with a wider range of data anomalies than are usually treated in one book, includes a discussion of detecting anomalies through generalized sensitivity analysis (GSA), a process of identifying inconsistencies using systematic and extensive comparisons of results obtained by analysis of exchangeable datasets or subsets. The book makes extensive use of real data, both in the form of a detailed analysis of a few real datasets and various published examples. Also included is a succinct introduction to functional equations that illustrates their utility in describing various forms of qualitative behavior for useful data characterizations.

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Feature Extraction and Image Processing

E-book Title : Feature Extraction and Image Processing
Author : Mark S. Nixon & Alberto S. Aguado
Publisher: Newnes
ISBN : 0 7506 5078 8

Overview :

We will no doubt be asked many times: why on earth write a new book on computer vision? Fair question: there are already many good books on computer vision already out in the bookshops, as you will find referenced later, so why add to them? Part of the answer is that any textbook is a snapshot of material that exists prior to it. Computer vision, the art of processing images stored within a computer, has seen a considerable amount of research by highly qualified people and the volume of research would appear to have increased in recent years. That means a lot of new techniques have been developed, and many of the more recent approaches have yet to migrate to textbooks.

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Dynamic Bayesian Networks: Representation, Inference and Learning

Title : Dynamic Bayesian Networks: Representation, Inference and Learning
Pub Date : 2002
Author : Kevin Patrick Murphy
Publisher: UNIVERSITY OF CALIFORNIA, BERKELEY
ISBN : -
Overview :
Abstract:

Modelling sequential data is important in many areas of science and engineering. Hidden Markov models (HMMs) and Kalman filter models (KFMs) are popular for this because they are simple and flexible. For example, HMMs have been used for speech recognition and bio-sequence analysis, and KFMs have been used for problems ranging from tracking planes and missiles to predicting the economy. However, HMMs and KFMs are limited in their “expressive power”. Dynamic Bayesian Networks (DBNs) generalize HMMs by allowing the state space to be represented in factored form, instead of as a single discrete random variable. DBNs generalize KFMs by allowing arbitrary probability distributions, not just (unimodal) linear-Gaussian. In this thesis, I will discuss how to represent many different kinds of models as DBNs, how to perform exact and approximate inference in DBNs, and how to learn DBN models from sequential data.

In particular, the main novel technical contributions of this thesis are as follows: a way of representing Hierarchical HMMs as DBNs, which enables inference to be done in O(T) time instead of O(T 3), where T is the length of the sequence; an exact smoothing algorithm that takes O(log T) space instead of O(T); a simple way of using the junction tree algorithm for online inference in DBNs; new complexity bounds on exact online inference in DBNs; a new deterministic approximate inference algorithm called factored frontier; an analysis of the relationship between the BK algorithm and loopy belief propagation; a way of applying Rao-Blackwellised particle filtering to DBNs in general, and the SLAM (simultaneous localization and mapping) problem in particular; a way of extending the structural EM algorithm to DBNs; and a variety of different applications of DBNs. However, perhaps the main value of the thesis is its catholic presentation of the field of sequential data modelling.

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Embedded Hardware Know It All

Embedded Hardware Know It All
Jack Ganssle, Tammy Noergaard, Fred Eady etal| Newnes| ISBN-10 : 0750685840| Pages : 456| PDF

Contents:
CHAPTER 1: Embedded Hardware Basics
CHAPTER 2: Logic Circuits
CHAPTER 3: Embedded Processors
CHAPTER 4: Embedded Board Buses and I/O
CHAPTER 5: Memory Systems
CHAPTER 6: Timing Analysis in Embedded Systems
CHAPTER 7: Chooosing a Microcontroller and Other Design Decisions
CHAPTER 8: The Essence of Microcontroller Networking: RS-232
CHAPTER 9: Interfacing to Sensors and Actuators
CHAPTER 10: Other Useful Hardware Design Tips and Techniques
APPENDIX A: Schematic Symbols
APPENDIX B: Acronyms and Abbreviations
APPENDIX C: PC Board Design Issues

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Programming Game AI by Example

Programming Game AI by Example
Wordware Publishing Inc.,U.S. (1 Oct 2004) | ISBN: 1556220782 | English | CHM | 8.69 Mb | 500 Pages

With the recent success of such games as Microsoft's Halo, artificial intelligence has taken a bigger role in the gaming industry and a few books have emerged with an academic, theoretical approach to the topic. AI Game Programming by Example describes in detail many of the AI techniques used in modern computer games.

Programming by Example describes in detail many of the AI techniques used in modern computer games and, more importantly, explicitly shows the reader how to implement these practical AI techniques within the framework of several popular game genres. These features, combined with the exercises throughout the book, provide game developers with a practical foundation to game AI.

Programming Game AI by Example provides a comprehensive and practical introduction to the "bread and butter" AI techniques used by the game development industry, leading the reader through the process of designing, programming, and implementing intelligent agents for action games using the C++ programming language.

Techniques covered include state- and goal-based behavior, inter-agent communication, individual and group steering behaviors, team AI, graph theory, search, path planning and optimization, triggers, scripting, scripted finite state machines, perceptual modeling, goal evaluation, goal arbitration, and fuzzy logic.

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Distributed Artificial Intelligence, Agent Technology, and Collaborative Applications

Cutting-edge developments in artificial intelligence are now driving applications that are only hinting at the level of value they will soon contribute to organizations, consumers, and societies across all domains.

Distributed Artificial Intelligence, Agent Technology, and Collaborative Applications offers an enriched set of research articles in artificial intelligence (AI), covering significant AI subjects such as information retrieval, conceptual modeling, supply chain demand forecasting, and machine learning algorithms. This comprehensive collection provides libraries with a one-stop resource to equip the academic, industrial, and managerial communities with an in-depth look into the most pertinent AI advances that will lead to the most valuable applications.

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Embedded Systems Architecture: A Comprehensive Guide for Engineers and Programmers

This comprehensive textbook provides a broad and in-depth overview of embedded systems architecture for engineering students and embedded systems professionals. The book is well suited for undergraduate embedded systems courses in electronics/electrical engineering and engineering technology (EET) departments in universities and colleges, as well as for corporate training of employees.

The book is a readable and practical guide covering embedded hardware, firmware, and applications. It clarifies all concepts with references to current embedded technology as it exists in the industry today, including many diagrams and applicable computer code. Among the topics covered in detail are:
· hardware components, including processors, memory, buses, and I/O
· system software, including device drivers and operating systems
· use of assembly language and high-level languages such as C and Java
· interfacing and networking
· case studies of real-world embedded designs
· applicable standards grouped by system application

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Embedded Software

Embedded software is present everywhere from a garage door opener to implanted medical devices to multicore computer systems. This book covers the development and testing of embedded software from many different angles and using different programming languages. Optimization of code, and the testing of that code, are detailed to enable readers to create the best solutions on-time and on-budget. Bringing together the work of leading experts in the field, this a comprehensive reference that every embedded developer will need!

Chapter 1: Basic Embedded Programming Concepts
Chapter 2: Device Drivers
Chapter 3: Embedded Operating Systems
Chapter 4: Networking
Chapter 5: Error Handling and Debugging
Chapter 6: Hardware/Software Co-Verification
Chapter 7: Techniques for Embedded Media Processing
Chapter 8: DSP in Embedded Systems
Chapter 9: Practical Embedded Coding Techniques
Chapter 10: Development Technologies and Trends

*Proven, real-world advice and guidance from such name authors as Tammy Noergard, Jen LaBrosse, and Keith Curtis
*Popular architectures and languages fully discussed
*Gives a comprehensive, detailed overview of the techniques and methodologies for developing effective, efficient embedded software

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Implementing 802.11 with Microcontrollers

This book is intended to provide you with everything you need to know to create and deploy a microcontroller-based 802.11b wireless network. You read it correctly, I did indeed say everything you need to know. I’ve spent the last year being rejected, ignored and hung up on. When I wasn’t being subjected to any of the aforementioned disrespectful acts, I was being lied to, promised to and conveniently forgotten. Some of the folks holding the 802.11b Holy Grail had no scruples and performed all of the despicable acts I’ve mentioned against my person. All of that angst was directed at me (or rather not directed at me) because I wanted to learn how to implement 802.11b in the world of microcontrollers. Well, I have seen the 802.11b light and I am here to spread the word to all in microcontrollerdom. 802.11b communication with inexpensive off-the-shelf microcontrollers

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Artificial Crime Analysis Systems: Using Computer Simulations and Geographic Information Systems

In the last decade there has been a phenomenal growth in interest in crime pattern analysis. Geographic information systems are now widely used in urban police agencies throughout industrial nations. With this, scholarly interest in understanding crime patterns has grown considerably.

Artificial Crime Analysis Systems: Using Computer Simulations and Geographic Information Systems discusses leading research on the use of computer simulation of crime patterns to reveal hidden processes of urban crimes, taking an interdisciplinary approach by combining criminology, computer simulation, and geographic information systems into one comprehensive resource.

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Robotics

This up-to-date text/reference is designed to present the fundamental principles of robotics with a strong emphasis on engineering applications and industrial solutions based on robotic technology. It can be used by practicing engineers and scientists -- or as a text in standard university courses in robotics. The book has extensive coverage of the major robotic classifications, including Wheeled Mobile Robots, Legged Robots, and the Robotic Manipulator. A central theme is the importance of kinematics to robotic principles. The book is accompanied by a CD-ROM with MATLAB simulations, third party applications, and more. FEATURES +Discusses the major robot classifications including Wheeled Mobile Robots, Legged Robots, and the Robotic Manipulator +Provides an introduction to basic mechanics and electronics; presents mathematical modeling concepts; and performs robotic simulations using MATLAB +Includes extensive coverage of kinematics, integrated throughout the book whenever appropriate +Includes a CD-ROM with demos, MATLAB simulations, and figures.

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