Developed from expert contributions to the first and second International Workshop on Machine Learning for Vision-Based Motion Analysis, this important text/reference highlights the latest algorithms and systems for robust and effective vision-based motion understanding from a machine learning perspective. Highlighting the benefits of collaboration between the communities of object motion understanding and machine learning, the book discusses the most active forefronts of research, including current challenges and potential future directions.
Topics and features: provides a comprehensive review of the latest developments in vision-based motion analysis, presenting numerous case studies on state-of-the-art learning algorithms; examines algorithms for clustering and segmentation, and manifold learning for dynamical models; describes the theory behind mixed-state statistical models, with a focus on mixed-state Markov models that take into account spatial and temporal interaction; discusses object tracking in surveillance image streams, discriminative multiple target tracking, and guidewire tracking in fluoroscopy; explores issues of modeling for saliency detection, human gait modeling, modeling of extremely crowded scenes, and behavior modeling from video surveillance data; investigates methods for automatic recognition of gestures in Sign Language, and human action recognition from small training sets.
Researchers, professional engineers, and graduate students in computer vision, pattern recognition and machine learning, will all find this text an accessible survey of machine learning techniques for vision-based motion analysis. The book will also be of interest to all who work with specific vision applications, such as surveillance, sport event analysis, healthcare, video conferencing, and motion video indexing and retrieval.
The authors begin by describing what patterns are and how they can help you design object-oriented software. They then go on to systematically name, explain, evaluate, and catalog recurring designs in object-oriented systems. With Design Patterns as your guide, you will learn how these important patterns fit into the software development process, and how you can leverage them to solve your own design problems most efficiently.
Each pattern describes the circumstances in which it is applicable, when it can be applied in view of other design constraints, and the consequences and trade-offs of using the pattern within a larger design. All patterns are compiled from real systems and are based on real-world examples. Each pattern also includes code that demonstrates how it may be implemented in object-oriented programming languages like C++ or Smalltalk.
Learning OpenCV puts you in the middle of the rapidly expanding field of computer vision. Written by the creators of the free open source OpenCV library, this book introduces you to computer vision and demonstrates how you can quickly build applications that enable computers to "see" and make decisions based on that data.
Computer vision is everywhere-in security systems, manufacturing inspection systems, medical image analysis, Unmanned Aerial Vehicles, and more. It stitches Google maps and Google Earth together, checks the pixels on LCD screens, and makes sure the stitches in your shirt are sewn properly. OpenCV provides an easy-to-use computer vision framework and a comprehensive library with more than 500 functions that can run vision code in real time.
Learning OpenCV will teach any developer or hobbyist to use the framework quickly with the help of hands-on exercises in each chapter. This book includes:A thorough introduction to OpenCVGetting input from camerasTransforming imagesSegmenting images and shape matchingPattern recognition, including face detectionTracking and motion in 2 and 3 dimensions3D reconstruction from stereo visionMachine learning algorithms
Getting machines to see is a challenging but entertaining goal. Whether you want to build simple or sophisticated vision applications, Learning OpenCV is the book you need to get started.
Programming Computer Vision with Python explains computer vision in broad terms that won’t bog you down in theory. You get complete code samples with explanations on how to reproduce and build upon each example, along with exercises to help you apply what you’ve learned. This book is ideal for students, researchers, and enthusiasts with basic programming and standard mathematical skills.Learn techniques used in robot navigation, medical image analysis, and other computer vision applicationsWork with image mappings and transforms, such as texture warping and panorama creationCompute 3D reconstructions from several images of the same sceneOrganize images based on similarity or content, using clustering methodsBuild efficient image retrieval techniques to search for images based on visual contentUse algorithms to classify image content and recognize objectsAccess the popular OpenCV library through a Python interface
With over 500 functions that span many areas in vision, OpenCV is used for commercial applications such as security, medical imaging, pattern and face recognition, robotics, and factory product inspection. This book gives you a firm grounding in computer vision and OpenCV for building simple or sophisticated vision applications. Hands-on exercises in each chapter help you apply what you’ve learned.
This volume covers the entire library, in its modern C++ implementation, including machine learning tools for computer vision.Learn OpenCV data types, array types, and array operationsCapture and store still and video images with HighGUITransform images to stretch, shrink, warp, remap, and repairExplore pattern recognition, including face detectionTrack objects and motion through the visual fieldReconstruct 3D images from stereo visionDiscover basic and advanced machine learning techniques in OpenCV
It includes Matlab code of the most common methods and algorithms in the book, together with a descriptive summary and solved examples, and including real-life data sets in imaging and audio recognition.
This text is designed for electronic engineering, computer science, computer engineering, biomedical engineering and applied mathematics students taking graduate courses on pattern recognition and machine learning as well as R&D engineers and university researchers in image and signal processing/analyisis, and computer vision.Matlab code and descriptive summary of the most common methods and algorithms in Theodoridis/Koutroumbas, Pattern Recognition, Fourth EditionSolved examples in Matlab, including real-life data sets in imaging and audio recognitionAvailable separately or at a special package price with the main text (ISBN for package: 978-0-12-374491-3)
3D Printing with Delta Printers contains detailed descriptions of the innovative delta design including unique hardware, software, and maintenance requirements. The book also covers tips for building your own delta printer as well as examples of common enhancements.
This book will enable you to build, configure, and enhance your delta printer. The topics covered will reveal the often-mysterious nuances of the delta design that will enable your printer to compete with the best of what your 3D printer friends can build.
This book introduces key game production concepts in an artist-friendly way, and rapidly teaches the basic scripting skills you'll need with Unity. It goes on to show how you, as an independent game artist, can create interactive games, ideal in scope for today's casual and mobile markets, while also giving you a firm foundation in game logic and design.
The first part of the book explains the logic involved in game interaction, and soon has you creating game assets through simple examples that you can build upon and gradually expand. In the second part, you'll build the foundations of a point-and-click style first-person adventure game—including reusable state management scripts, dialogue trees for character interaction, load/save functionality, a robust inventory system, and a bonus feature: a dynamically configured maze and mini-map. With the help of the provided 2D and 3D content, you'll learn to evaluate and deal with challenges in bite-sized pieces as the project progresses, gaining valuable problem-solving skills in interactive design. By the end of the book, you will be able to actively use the Unity 3D game engine, having learned the necessary workflows to utilize your own assets. You will also have an assortment of reusable scripts and art assets with which to build future games.
· Thoroughly developed to include many more worked examples to give greater understanding of the various methods and techniques
· Many more diagrams included--now in two color--to provide greater insight through visual presentation
· Matlab code of the most common methods are given at the end of each chapter.
· More Matlab code is available, together with an accompanying manual, via this site
· Latest hot topics included to further the reference value of the text including non-linear dimensionality reduction techniques, relevance feedback, semi-supervised learning, spectral clustering, combining clustering algorithms.
· An accompanying book with Matlab code of the most common methods and algorithms in the book, together with a descriptive summary, and solved examples including real-life data sets in imaging, and audio recognition. The companion book will be available separately or at a special packaged price (ISBN: 9780123744869).Thoroughly developed to include many more worked examples to give greater understanding of the various methods and techniques Many more diagrams included--now in two color--to provide greater insight through visual presentation Matlab code of the most common methods are given at the end of each chapter An accompanying book with Matlab code of the most common methods and algorithms in the book, together with a descriptive summary and solved examples, and including real-life data sets in imaging and audio recognition. The companion book is available separately or at a special packaged price (Book ISBN: 9780123744869. Package ISBN: 9780123744913) Latest hot topics included to further the reference value of the text including non-linear dimensionality reduction techniques, relevance feedback, semi-supervised learning, spectral clustering, combining clustering algorithms Solutions manual, powerpoint slides, and additional resources are available to faculty using the text for their course. Register at www.textbooks.elsevier.com and search on "Theodoridis" to access resources for instructor.
Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how.
By using concrete examples, minimal theory, and two production-ready Python frameworks—scikit-learn and TensorFlow—author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You’ll learn a range of techniques, starting with simple linear regression and progressing to deep neural networks. With exercises in each chapter to help you apply what you’ve learned, all you need is programming experience to get started.Explore the machine learning landscape, particularly neural netsUse scikit-learn to track an example machine-learning project end-to-endExplore several training models, including support vector machines, decision trees, random forests, and ensemble methodsUse the TensorFlow library to build and train neural netsDive into neural net architectures, including convolutional nets, recurrent nets, and deep reinforcement learningLearn techniques for training and scaling deep neural netsApply practical code examples without acquiring excessive machine learning theory or algorithm details
Peter Christen’s book is divided into three parts: Part I, “Overview”, introduces the subject by presenting several sample applications and their special challenges, as well as a general overview of a generic data matching process. Part II, “Steps of the Data Matching Process”, then details its main steps like pre-processing, indexing, field and record comparison, classification, and quality evaluation. Lastly, part III, “Further Topics”, deals with specific aspects like privacy, real-time matching, or matching unstructured data. Finally, it briefly describes the main features of many research and open source systems available today.By providing the reader with a broad range of data matching concepts and techniques and touching on all aspects of the data matching process, this book helps researchers as well as students specializing in data quality or data matching aspects to familiarize themselves with recent research advances and to identify open research challenges in the area of data matching. To this end, each chapter of the book includes a final section that provides pointers to further background and research material. Practitioners will better understand the current state of the art in data matching as well as the internal workings and limitations of current systems. Especially, they will learn that it is often not feasible to simply implement an existing off-the-shelf data matching system without substantial adaption and customization. Such practical considerations are discussed for each of the major steps in the data matching process.
New features of the 2nd Edition:Contains more than 1000 new terms, notably an increased focus on image processing and machine vision terms; Includes the addition of reference links across the majority of terms pointing readers to further information about the concept under discussion so that they can continue to expand their understanding; Now available as an eBook with enhanced content: approximately 50 videos to further illustrate specific terms; active cross-linking between terms so that readers can easily navigate from one related term to another and build up a full picture of the topic in question; and hyperlinked references to fully embed the text in the current literature.
After providing the fundamentals for ISAR imaging, the book gives the detailed imaging procedures for ISAR imaging with associated MATLAB functions and codes. To enhance the image quality in ISAR imaging, several imaging tricks and fine-tuning procedures such as zero-padding and windowing are also presented. Finally, various real applications of ISAR imagery, like imaging the antenna-platform scattering, are given in a separate chapter. For all these algorithms, MATLAB codes and figures are included. The final chapter considers advanced concepts and trends in ISAR imaging.
Liu has written a comprehensive text on Web mining, which consists of two parts. The first part covers the data mining and machine learning foundations, where all the essential concepts and algorithms of data mining and machine learning are presented. The second part covers the key topics of Web mining, where Web crawling, search, social network analysis, structured data extraction, information integration, opinion mining and sentiment analysis, Web usage mining, query log mining, computational advertising, and recommender systems are all treated both in breadth and in depth. His book thus brings all the related concepts and algorithms together to form an authoritative and coherent text.
The book offers a rich blend of theory and practice. It is suitable for students, researchers and practitioners interested in Web mining and data mining both as a learning text and as a reference book. Professors can readily use it for classes on data mining, Web mining, and text mining. Additional teaching materials such as lecture slides, datasets, and implemented algorithms are available online.
As fields like communications, speech and image processing, and related areas are rapidly developing, the FFT as one of the essential parts in digital signal processing has been widely used. Thus there is a pressing need from instructors and students for a book dealing with the latest FFT topics.
Fast Fourier Transform - Algorithms and Applications provides a thorough and detailed explanation of important or up-to-date FFTs. It also has adopted modern approaches like MATLAB examples and projects for better understanding of diverse FFTs.
Fast Fourier Transform - Algorithms and Applications is designed for senior undergraduate and graduate students, faculty, engineers, and scientists in the field, and self-learners to understand FFTs and directly apply them to their fields, efficiently. It is designed to be both a text and a reference. Thus examples, projects and problems all tied with MATLAB, are provided for grasping the concepts concretely. It also includes references to books and review papers and lists of applications, hardware/software, and useful websites. By including many figures, tables, bock diagrams and graphs, this book helps the reader understand the concepts of fast algorithms readily and intuitively. It provides new MATLAB functions and MATLAB source codes. The material in Fast Fourier Transform - Algorithms and Applications is presented without assuming any prior knowledge of FFT. This book is for any professional who wants to have a basic understanding of the latest developments in and applications of FFT. It provides a good reference for any engineer planning to work in this field, either in basic implementation or in research and development.
This important guide/reference presents a comprehensive overview of medical image analysis. Highly practical in its approach, the text is uniquely structured by potential applications, supported by exercises throughout. Each of the key concepts are introduced in a concise manner, allowing the reader to understand the interdependencies between them before exploring the deeper details and derivations.
Topics and features: presents learning objectives, exercises and concluding remarks in each chapter, in addition to a glossary of abbreviations; describes a range of common imaging techniques, reconstruction techniques and image artefacts; discusses the archival and transfer of images, including the HL7 and DICOM standards; presents a selection of techniques for the enhancement of contrast and edges, for noise reduction and for edge-preserving smoothing; examines various feature detection and segmentation techniques, together with methods for computing a registration or normalisation transformation; explores object detection, as well as classification based on segment attributes such as shape and appearance; reviews the validation of an analysis method; includes appendices on Markov random field optimization, variational calculus and principal component analysis.
This easy-to-follow, classroom-tested textbook is ideal for undergraduate and graduate courses on medical image analysis and related subjects – with possible course outlines suggested in the Preface. The work can also be used as a self-study guide for professionals in medical imaging technology, and for computer scientists and engineers wishing to specialise in medical applications.
The main thrust of the material is analog circuitry, focusing on fundamental principles of transistors, integrated circuit and vacuum tube-based amplifier operation and theory, and operation of typical guitar signal processing effects circuits. Updated to the new edition include:
• New coverage of tone control circuits, MOSFETS and their applications as small-signal amplifiers, rail splitters and charge pumps, amplifiers using germanium transistors, and tube power amp design
• Expanded coverage of numerous subjects such as vacuum tube power supplies, the digital oscilloscope, Darlington and Sziklai transistors, and signal spectra and transfer function symmetry
• Additional examples of various circuits such as overdrive, distortion, chorus, delay, tremolo and auto-wah circuits as well as amplifier design
Electronics for Guitarists is ideal for the musician or engineer interested in analog signal processing. The material is also useful to general electronics hobbyists, technologists and engineers with an interest in guitar and music-related electronics applications.
If you want to do computational photography and computer vision on Apple's mobile devices, then this book is for you. No previous experience with app development or OpenCV is required. However, basic knowledge of C++ or Objective-C is recommended.What You Will LearnUse Xcode and Interface Builder to develop iOS appsObtain OpenCV's standard modules and build extra modules from sourceControl all the parameters of the iOS device's cameraCapture, save, and share photos and videosAnalyze colors, shapes, and textures in ordinary and specialized photographsBlend and compare images to create special photographic effects and augmented reality toolsDetect faces and morph facial featuresClassify coins and other objectsIn Detail
iOS Application Development with OpenCV 3 enables you to turn your smartphone camera into an advanced tool for photography and computer vision. Using the highly optimized OpenCV library, you will process high-resolution images in real time. You will locate and classify objects, and create models of their geometry. As you develop photo and augmented reality apps, you will gain a general understanding of iOS frameworks and developer tools, plus a deeper understanding of the camera and image APIs.
After completing the book's four projects, you will be a well-rounded iOS developer with valuable experience in OpenCV.Style and approach
The book is practical, creative, and precise. It shows you the steps to create and customize five projects that solve important problems for beginners in mobile app development and computer vision. Complete source code and numerous visual aids are included in each chapter. Experimentation is an important part of the book. You will use computer vision to explore the real world, and then you will refine the projects based on your findings.
The new edition includes: modifications to about 30-40% of the end of chapter problems; a new introduction to electromagnetics based on behavior of charges; a new section on units; MATLAB tools for solution of problems and demonstration of subjects; most chapters include a summary. The book is an undergraduate textbook at the Junior level, intended for required classes in electromagnetics. It is written in simple terms with all details of derivations included and all steps in solutions listed. It requires little beyond basic calculus and can be used for self-study. The wealth of examples and alternative explanations makes it very approachable by students.
· More than 400 examples and exercises, exercising every topic in the book
· · Includes 600 end-of-chapter problems, many of them applications or simplified applications
· · Discusses the finite element, finite difference and method of moments in a dedicated chapter
Additional highlights include:
- Fundamental information on communications, signal and system theories
- Coverage of superheterodyne, direct-conversion, low-IF, and band-pass sampling radio architectures
- Frequency planning, system link budgeting, and performance evaluation of transmitters and receivers
- Nonlinearity effect analyses involving intermodulation, interferer blocking, spectrum regrowth and modulation
- Approaches for specifying RF ASICs on which mobile systems are built
- AGC systems, ADC dynamic range consideration and power management are addressed
- In-depth treatment of both theoretical and practical aspects of mobile station RF system design
This comprehensive reference work covers a wide range of topics from general principles of communication theory, as it applies to digital radio designs to specific examples on implementing multimode mobile systems. Wireless engineering professionals will definitely find this an invaluable reference book.
This book is unique in that it gives readers the skills necessary for obtaining excellent images for scientific purposes in a concise and procedurally oriented manner. This not only gets the reader used to a disciplined approach to imaging to maximize quality, but also to maximize the success (and minimize the frustration!) inherent in the pursuit of astrophotography. The knowledge and skills imparted to the reader of this handbook also provide an excellent basis for “beautiful picture” astrophotography!
There is a wealth of information in this book – a distillation of ideas and data presented by a diverse set of sources and based on the most recent techniques, equipment, and data available to the amateur astronomer. There are also numerous practical exercises. Scientific Astrophotography is perfect for any amateur astronomer who wants to go beyond just astrophotography and actually contribute to the science of astronomy.
The book covers the full range of the state of the art of NPR with every chapter authored by internationally renowned experts in the field, covering both classical and contemporary techniques. It will enable both graduate students in computer graphics, computer vision or image processing and professional developers alike to quickly become familiar with contemporary techniques, enabling them to apply 2D NPR algorithms in their own projects.
Written by leading experts in the field, this book presents a unique practical perspective of state-of-the-art microscope image processing and the development of specialized algorithms. It contains in-depth analysis of methods coupled with the results of specific real-world experiments. Microscope Image Processing covers image digitization and display, object measurement and classification, autofocusing, and structured illumination.
Key Features:Detailed descriptions of many leading-edge methods and algorithmsIn-depth analysis of the method and experimental results, taken from real-life examplesEmphasis on computational and algorithmic aspects of microscope image processingAdvanced material on geometric, morphological, and wavelet image processing, fluorescence, three-dimensional and time-lapse microscopy, microscope image enhancement, MultiSpectral imaging, and image data management
This book is of interest to all scientists, engineers, clinicians, post-graduate fellows, and graduate students working in the fields of biology, medicine, chemistry, pharmacology, and other related fields. Anyone who uses microscopes in their work and needs to understand the methodologies and capabilities of the latest digital image processing techniques will find this book invaluable.Presents a unique practical perspective of state-of-the-art microcope image processing and the development of specialized algorithmsEach chapter includes in-depth analysis of methods coupled with the results of specific real-world experimentsCo-edited by Kenneth R. Castleman, world-renowned pioneer in digital image processing and author of two seminal textbooks on the subject
The author presents the first extended treatment of MM algorithms, which are ideal for high-dimensional optimization problems in data mining, imaging, and genomics; derives numerous algorithms from a broad diversity of application areas, with a particular emphasis on statistics, biology, and data mining; and summarizes a large amount of literature that has not reached book form before.
Video decoding is an example of an application domain with increasing computational requirements every new generation. This is due, on the one hand, to the trend towards high quality video systems (high definition and frame rate, 3D displays, etc) that results in a continuous increase in the amount of data that has to be processed in real-time. On the other hand, there is the requirement to maintain high compression efficiency which is only possible with video codes like H.264/AVC that use advanced coding techniques.
In this book, the parallelization of H.264/AVC decoding is presented as a case study of parallel programming. H.264/AVC decoding is an example of a complex application with many levels of dependencies, different kernels, and irregular data structures. The book presents a detailed methodology for parallelization of this type of applications. It begins with a description of the algorithm, an analysis of the data dependencies and an evaluation of the different parallelization strategies. Then the design and implementation of a novel parallelization approach is presented that is scalable to many core architectures. Experimental results on different parallel architectures are discussed in detail. Finally, an outlook is given on parallelization opportunities in the upcoming HEVC standard.
Due to its inherent time-scale locality characteristics, the discrete wavelet transform (DWT) has received considerable attention in digital signal processing (speech and image processing), communication, computer science and mathematics. Wavelet transforms are known to have excellent energy compaction characteristics and are able to provide perfect reconstruction. Therefore, they are ideal for signal/image processing. The shifting (or translation) and scaling (or dilation) are unique to wavelets. Orthogonality of wavelets with respect to dilations leads to multigrid representation.
The nature of wavelet computation forces us to carefully examine the implementation methodologies. As the computation of DWT involves filtering, an efficient filtering process is essential in DWT hardware implementation. In the multistage DWT, coefficients are calculated recursively, and in addition to the wavelet decomposition stage, extra space is required to store the intermediate coefficients. Hence, the overall performance depends significantly on the precision of the intermediate DWT coefficients.This work presents new implementation techniques of DWT, that are efficient in terms of computation requirement, storage requirement, and with better signal-to-noise ratio in the reconstructed signal.
Creative professionals who seek the fastest, easiest, most comprehensive way to learn Adobe Illustrator CC (2015 release) choose this Classroom in a Book® from the best-selling series of hands-on software training workbooks. This series offers what no other book or training program does—an official training series from Adobe Systems Incorporated, developed with the support of Adobe product experts.
Adobe Illustrator CC Classroom in a Book (2015 release) contains 15 lessons that cover the basics and beyond, providing countless tips and techniques to help you become more productive with the program. You can follow the book from start to finish or choose only those lessons that interest you. As with all Classroom in a Book products, online companion files include all the necessary assets you need to complete the projects featured in each lesson.
Build a strong foundation for working with Adobe Illustrator CC, by following hands-on projects for creating logos, illustrations, and posters. Learn how to use the Shaper tool and Live Shapes along with dynamic symbols to streamline graphics creation. Create website assets and export them in SVG format to support modern responsive web designs. From exacting illustration to more free-form painting, you’ll gain vital Illustrator skills as you progress through the lessons.
What you need to use this book: Adobe Illustrator CC (2015 release) software, for either Windows or Mac OS. (Software not included.)
Classroom in a Book®, the best-selling series of hands-on software training workbooks, offers what no other book or training program does—an official training series from Adobe Systems Incorporated, developed with the support of Adobe product experts.
Adobe Photoshop CC Classroom in a Book contains 14 lessons that cover the basics, providing countless tips and techniques to help you become more productive with the program. You can follow the book from start to finish or choose only those lessons that interest you.
Purchasing this book gives you access to the downloadable lesson files you need to work through the projects in the book, and to electronic book updates covering new features that Adobe releases for Creative Cloud customers. For access, goto www.peachpit.com/redeem and redeem the unique code provided inside this book.
“The Classroom in a Book series is by far the best training material on the market. Everything you need to master the software is included: clear explanations of each lesson, step-by-step instructions, and the project files for the students.”
Adobe Certified Instructor
Rocky Mountain Training
The book proposes novel 3D feature representations called Point Feature Histograms (PFH), as well as a frameworks for the acquisition and processing of Semantic 3D Object Maps with contributions to robust registration, fast segmentation into regions, and reliable object detection, categorization, and reconstruction. These contributions have been fully implemented and empirically evaluated on different robotic systems, and have been the original kernel to the widely successful open-source project the Point Cloud Library (PCL) -- see http://pointclouds.org.
What is one-shot color imaging? Typically, astronomical cooled-chip CCD cameras record only one color at a time - rather like old-fashioned black & white cameras fitted with color filters. Three images are taken in sequence - in red, blue, and green light - and these are then merged by software in a PC to form a color image. Each of the three images must be taken separately through a suitable color filter, which means that the total exposure time for every object is more than tripled. When exposure times can run into tens of minutes or even hours for each of the three colors, this can be a major drawback for the time-pressed amateur.
"One-Shot Color Astronomical Imaging" describes the most cost-effective and time-efficient way for any amateur astronomer to begin to photograph the deep-sky.
Creative professionals seeking the fastest, easiest, most comprehensive way to learn Adobe Photoshop CS5 choose Adobe Photoshop CS5 Classroom in a Book from the Adobe Creative Team at Adobe Press. The 14 project-based lessons in this book show readers step-by-step the key techniques for working in Photoshop CS5.
In addition to learning the key elements of the Photoshop interface, this completely revised CS5 edition shows readers how to edit images with precise selection control, correct a wide range of lens-based errors, interactively transform their images with the new Puppet Warp tool, and easily remove or replace image elements with the new Content-Aware Fill mode. The book also covers new powerful painting effects to artistically enhance images and shows how to combine multiple exposures into a single HDR image.
For the first time, the companion DVD will feature, in addition to the lesson files, 2 hours of free video tutorials from Learn Adobe Photoshop CS5 by Video by Adobe Press and video2brain, a great added value!
“The Classroom in a Book series is by far the best training material on the market. Everything you need to master the software is included: clear explanations of each lesson, step-by-step instructions, and the project files for the students.” –Barbara Binder, Adobe Certified Instructor, Rocky Mountain Training.
Classroom in a Book®, the best-selling series of hands-on software training workbooks, helps you learn the features of Adobe software quickly and easily. Classroom in a Book offers what no other book or training program does–an official training series from Adobe Systems Incorporated, developed with the support of Adobe product experts.
All of Peachpit's eBooks contain the same content as the print edition. You will find a link in the last few pages of your eBook that directs you to the media files.
If you are able to search the book, search for "Where are the lesson files?" Go to the very last page of the book and scroll backwards. You will need a web-enabled device or computer in order to access the media files that accompany this ebook.
Entering the URL supplied into a computer with web access will allow you to get to the files. Depending on your device, it is possible that your display settings will cut off part of the URL. To make sure this is not the case, try reducing your font size and turning your device to a landscape view. This should cause the full URL to appear.