For several decades researchers have tried to construct perception systems based on the registration data from video cameras. This work has produced various tools that have made recent advances possible in this area. Part 1 of this book deals with the problem of the calibration and auto-calibration of video captures. Part 2 is essentially concerned with the estimation of the relative object/capture position when a priori information is introduced (the CAD model of the object). Finally, Part 3 discusses the inference of density information and the shape recognition in images.

An engrossing guide to seeing—and communicating—more clearly from the groundbreaking course that helps FBI agents, cops, CEOs, ER docs, and others save money, reputations, and lives. How could looking at Monet’s water lily paintings help save your company millions? How can checking out people’s footwear foil a terrorist attack? How can your choice of adjective win an argument, calm your kid, or catch a thief? In her celebrated seminar, the Art of Perception, art historian Amy Herman has trained experts from many fields how to perceive and communicate better. By showing people how to look closely at images, she helps them hone their “visual intelligence,” a set of skills we all possess but few of us know how to use properly. She has spent more than a decade teaching doctors to observe patients instead of their charts, helping police officers separate facts from opinions when investigating a crime, and training professionals from the FBI, the State Department, Fortune 500 companies, and the military to recognize the most pertinent and useful information. Her lessons highlight far more than the physical objects you may be missing; they teach you how to recognize the talents, opportunities, and dangers that surround you every day. Whether you want to be more effective on the job, more empathetic toward your loved ones, or more alert to the trove of possibilities and threats all around us, this book will show you how to see what matters most to you more clearly than ever before. Please note: this ebook contains full-color art reproductions and photographs, and color is at times essential to the observation and analysis skills discussed in the text. For the best reading experience, this ebook should be viewed on a color device.

The hand is quicker than the eye. In many cases, so is digital video. Maintaining image quality in bandwidth- and memory-restricted environments is quickly becoming a reality as thriving research delves ever deeper into perceptual coding techniques, which discard superfluous data that humans cannot process or detect. Surveying the topic from a Human Visual System (HVS)-based approach, Digital Video Image Quality and Perceptual Coding outlines the principles, metrics, and standards associated with perceptual coding, as well as the latest techniques and applications. This book is divided broadly into three parts. First, it introduces the fundamental theory, concepts, principles, and techniques underlying the field, such as the basics of compression, HVS modeling, and coding artifacts associated with current well-known techniques. The next section focuses on picture quality assessment criteria; subjective and objective methods and metrics, including vision model based digital video impairment metrics; testing procedures; and international standards regarding image quality. Finally, practical applications come into focus, including digital image and video coder designs based on the HVS as well as post-filtering, restoration, error correction, and concealment techniques. The permeation of digital images and video throughout the world cannot be understated. Nor can the importance of preserving quality while using minimal storage space, and Digital Video Image Quality and Perceptual Coding provides the tools necessary to accomplish this goal. Instructors and lecturers wishing to make use of this work as a textbook can download a presentation of 786 slides in PDF format organized to augment the text. accompany our book (H.R. Wu and K.R. Rao, Digital Video Image Quality and Perceptual Coding, CRC Press (ISBN: 0-8247-2777-0), Nov. 2005) for lecturers or instructor to use for their classes if they use the book.

When you look at an image, what do you see and feel? What do you want your audience to see and feel when they view your work? For over thirty years, Dr. Richard Zakia helped thousands of photographers hone in on their creative vision through the inspirational, informative text and images included in his classic book, Perception and Imaging. More than a step-by-step photography instruction manual, Perception and Imaging explores the fundamental act of photography – seeing – through a uniquely comprehensive combination of technique, history, visual perception, philosophy and psychology. No matter your level of technical skill, you can learn to think more clearly about what you wish to convey in your images. Fully revised to account for the unique influences and consequences of the digital revolution and online photosharing, John Suler newly addresses digital impermanence, sensory and cognitive overload, and the selfie, and their effects on perception. Additional coverage also includes microexpressions, Rorschach inkblots and subliminal reactions, transference, and synectics.

This textbook presents the main principles of visual analytics and describes techniques and approaches that have proven their utility and can be readily reproduced. Special emphasis is placed on various instructive examples of analyses, in which the need for and the use of visualisations are explained in detail. The book begins by introducing the main ideas and concepts of visual analytics and explaining why it should be considered an essential part of data science methodology and practices. It then describes the general principles underlying the visual analytics approaches, including those on appropriate visual representation, the use of interactive techniques, and classes of computational methods. It continues with discussing how to use visualisations for getting aware of data properties that need to be taken into account and for detecting possible data quality issues that may impair the analysis. The second part of the book describes visual analytics methods and workflows, organised by various data types including multidimensional data, data with spatial and temporal components, data describing binary relationships, texts, images and video. For each data type, the specific properties and issues are explained, the relevant analysis tasks are discussed, and appropriate methods and procedures are introduced. The focus here is not on the micro-level details of how the methods work, but on how the methods can be used and how they can be applied to data. The limitations of the methods are also discussed and possible pitfalls are identified. The textbook is intended for students in data science and, more generally, anyone doing or planning to do practical data analysis. It includes numerous examples demonstrating how visual analytics techniques are used and how they can help analysts to understand the properties of data, gain insights into the subject reflected in the data, and build good models that can be trusted. Based on several years of teaching related courses at the City, University of London, the University of Bonn and TU Munich, as well as industry training at the Fraunhofer Institute IAIS and numerous summer schools, the main content is complemented by sample datasets and detailed, illustrated descriptions of exercises to practice applying visual analytics methods and workflows.

Visual Perception and Control of Underwater Robots covers theories and applications from aquatic visual perception and underwater robotics. Within the framework of visual perception for underwater operations, image restoration, binocular measurement, and object detection are addressed. More specifically, the book includes adversarial critic learning for visual restoration, NSGA-II-based calibration for binocular measurement, prior knowledge refinement for object detection, analysis of temporal detection performance, as well as the effect of the aquatic data domain on object detection. With the aid of visual perception technologies, two up-to-date underwater robot systems are demonstrated. The first system focuses on underwater robotic operation for the task of object collection in the sea. The second is an untethered biomimetic robotic fish with a camera stabilizer, its control methods based on visual tracking. The authors provide a self-contained and comprehensive guide to understand underwater visual perception and control. Bridging the gap between theory and practice in underwater vision, the book features implementable algorithms, numerical examples, and tests, where codes are publicly available. Additionally, the mainstream technologies covered in the book include deep learning, adversarial learning, evolutionary computation, robust control, and underwater bionics. Researchers, senior undergraduate and graduate students, and engineers dealing with underwater visual perception and control will benefit from this work.

This second edition of the fully revised and updated From Photon to Pixel presents essential elements in modern digital photographic devices. Our universal infatuation with photography profoundly affects its usage and development. While some sides of photographic “culture” remain wholly unchanged – art photography, journalistic and advertising photography, scientific photography, etc. – new facets emerge: leisure or travel photography, everyday life photography, anecdotal, observational or unusual photography, and microcosm, or micro-community, photography with its culmination in the narcissistic selfie. These new forms combine an often simplified manner of photographing and modern means of instantaneous, remote and mass communication. This book does not extend into the sociological study of photography, instead it explains how the digital camera works by examining in detail each of the components that constitutes it to provide the reader with a preliminary guide into the inner workings of this device.

This book provides an introduction to human visual perception suitable for readers studying or working in the fields of computer graphics and visualization, cognitive science, and visual neuroscience. It focuses on how computer graphics images are generated, rather than solely on the organization of the visual system itself; therefore, the text pro

Computer Imaging: Digital Image Analysis and Processing brings together analysis and processing in a unified framework, providing a valuable foundation for understanding both computer vision and image processing applications. Taking an engineering approach, the text integrates theory with a conceptual and application-oriented style, allowing you to immediately understand how each topic fits into the overall structure of practical application development. Divided into five major parts, the book begins by introducing the concepts and definitions necessary to understand computer imaging. The second part describes image analysis and provides the tools, concepts, and models required to analyze digital images and develop computer vision applications. Part III discusses application areas for the processing of images, emphasizing human visual perception. Part IV delivers the information required to apply a CVIPtools environment to algorithm development. The text concludes with appendices that provide supplemental imaging information and assist with the programming exercises found in each chapter. The author presents topics as needed for understanding each practical imaging model being studied. This motivates the reader to master the topics and also makes the book useful as a reference. The CVIPtools software integrated throughout the book, now in a new Windows version, provides practical examples and encourages you to conduct additional exploration via tutorials and programming exercises provided with each chapter.

In ultrasound imaging and video visual perception is hindered by speckle multiplicative noise that degrades the quality. Noise reduction is therefore essential for improving the visual observation quality or as a pre-processing step for further automated analysis, such as image/video segmentation, texture analysis and encoding in ultrasound imaging and video. The goal of the first book (book 1 of 2 books) was to introduce the problem of speckle in ultrasound image and video as well as the theoretical background, algorithmic steps, and the MatlabTM for the following group of despeckle filters: linear despeckle filtering, non-linear despeckle filtering, diffusion despeckle filtering, and wavelet despeckle filtering. The goal of this book (book 2 of 2 books) is to demonstrate the use of a comparative evaluation framework based on these despeckle filters (introduced on book 1) on cardiovascular ultrasound image and video processing and analysis. More specifically, the despeckle filtering evaluation framework is based on texture analysis, image quality evaluation metrics, and visual evaluation by experts. This framework is applied in cardiovascular ultrasound image/video processing on the tasks of segmentation and structural measurements, texture analysis for differentiating between two classes (i.e. normal vs disease) and for efficient encoding for mobile applications. It is shown that despeckle noise reduction improved segmentation and measurement (of tissue structure investigated), increased the texture feature distance between normal and abnormal tissue, improved image/video quality evaluation and perception and produced significantly lower bitrates in video encoding. Furthermore, in order to facilitate further applications we have developed in MATLABTM two different toolboxes that integrate image (IDF) and video (VDF) despeckle filtering, texture analysis, and image and video quality evaluation metrics. The code for these toolsets is open source and these are available to download complementary to the two monographs.