This book constitutes the refereed proceedings of CVM 2012, the First International Conference on Computational Visual Media, held in Beijing, China, in November 2012. The 33 revised full papers were carefully reviewed and selected from 81 submissions. The papers are organized in topical sections on image processing I and II, geometric processing, saliency, recognition, perception and learning, shape analysis, media retrieval, and capture, rendering and visualization.

Captain Kirk fought Nazis. JFK's assassination is a videogame touchstone. And there's no history like "Drunk History."

Advances in computing and communications have brought about an increasing demand for visual information. Visual Computing addresses the principles behind "visual technology", and provides readers with a good understanding of how the integration of Computer Graphics, Visual Perception and Imaging is achieved. Included in the book is an overview of important research areas within this integration which will be useful for further work in the field. Foundations of visual perception and psychophysics are presented as well as basic methods of imaging and computer vision. This book serves as an excellent reference and textbook for those who wish to apply or study "visual computing technology."

This text provides an introduction to computational aspects of early vision, in particular, color, stereo, and visual navigation. It integrates approaches from psychophysics and quantitative neurobiology, as well as theories and algorithms from machine vision and photogrammetry. When presenting mathematical material, it uses detailed verbal descriptions and illustrations to clarify complex points. The text is suitable for upper-level students in neuroscience, biology, and psychology who have basic mathematical skills and are interested in studying the mathematical modeling of perception.

The more than twenty contributions in this book, all new and previously unpublished, provide an up-to-date survey of contemporary research on computational modeling of the visual system. The approaches represented range from neurophysiology to psychophysics, and from retinal function to the analysis of visual cues to motion, color, texture, and depth. The contributions are linked thematically by a consistent consideration of the links between empirical data and computational models in the study of visual function. An introductory chapter by Edward Adelson and James Bergen gives a new and elegant formalization of the elements of early vision. Subsequent sections treat receptors and sampling, models of neural function, detection and discrimination, color and shading, motion and texture, and 3D shape. Each section is introduced by a brief topical review and summary. ContributorsEdward H. Adelson, Albert J. Ahumada, Jr., James R. Bergen, David G. Birch, David H. Brainard, Heinrich H. Bülthoff, Charles Chubb, Nancy J. Coletta, Michael D'Zmura, John P. Frisby, Norma Graham, Norberto M. Grzywacz, P. William Haake, Michael J. Hawken, David J. Heeger, Donald C. Hood, Elizabeth B. Johnston, Daniel Kersten, Michael S. Landy, Peter Lennie, J. Stephen Mansfield, J. Anthony Movshon, Jacob Nachmias, Andrew J. Parker, Denis G. Pelli, Stephen B. Pollard, R. Clay Reid, Robert Shapley, Carlo L. M. Tiana, Brian A. Wandell, Andrew B. Watson, David R. Williams, Hugh R. Wilson, Yuede. Yang, Alan L. Yuille

The derivation, exposition, and justification of the Selective Tuning model of vision and attention.

Introduction to Visual Computing: Core Concepts in Computer Vision, Graphics, and Image Processing covers the fundamental concepts of visual computing. Whereas past books have treated these concepts within the context of specific fields such as computer graphics, computer vision or image processing, this book offers a unified view of these core concepts, thereby providing a unified treatment of computational and mathematical methods for creating, capturing, analyzing and manipulating visual data (e.g. 2D images, 3D models). Fundamentals covered in the book include convolution, Fourier transform, filters, geometric transformations, epipolar geometry, 3D reconstruction, color and the image synthesis pipeline. The book is organized in four parts. The first part provides an exposure to different kinds of visual data (e.g. 2D images, videos and 3D geometry) and the core mathematical techniques that are required for their processing (e.g. interpolation and linear regression.) The second part of the book on Image Based Visual Computing deals with several fundamental techniques to process 2D images (e.g. convolution, spectral analysis and feature detection) and corresponds to the low level retinal image processing that happens in the eye in the human visual system pathway. The next part of the book on Geometric Visual Computing deals with the fundamental techniques used to combine the geometric information from multiple eyes creating a 3D interpretation of the object and world around us (e.g. transformations, projective and epipolar geometry, and 3D reconstruction). This corresponds to the higher level processing that happens in the brain combining information from both the eyes thereby helping us to navigate through the 3D world around us. The last two parts of the book cover Radiometric Visual Computing and Visual Content Synthesis. These parts focus on the fundamental techniques for processing information arising from the interaction of light with objects around us, as well as the fundamentals of creating virtual computer generated worlds that mimic all the processing presented in the prior sections. The book is written for a 16 week long semester course and can be used for both undergraduate and graduate teaching, as well as a reference for professionals.

The Research Handbook on Visual Politics focuses on key theories and methodologies for better understanding visual political communication. It also concentrates on the depictions of power within politics, taking a historical and longitudinal approach to the topic of placing visuals within a wider framework of political understanding.

Computational photography refers broadly to imaging techniques that enhance or extend the capabilities of digital photography. This new and rapidly developing research field has evolved from computer vision, image processing, computer graphics and applied optics—and numerous commercial products capitalizing on its principles have already appeared in diverse market applications, due to the gradual migration of computational algorithms from computers to imaging devices and software. Computational Photography: Methods and Applications provides a strong, fundamental understanding of theory and methods, and a foundation upon which to build solutions for many of today's most interesting and challenging computational imaging problems. Elucidating cutting-edge advances and applications in digital imaging, camera image processing, and computational photography, with a focus on related research challenges, this book: Describes single capture image fusion technology for consumer digital cameras Discusses the steps in a camera image processing pipeline, such as visual data compression, color correction and enhancement, denoising, demosaicking, super-resolution reconstruction, deblurring, and high dynamic range imaging Covers shadow detection for surveillance applications, camera-driven document rectification, bilateral filtering and its applications, and painterly rendering of digital images Presents machine-learning methods for automatic image colorization and digital face beautification Explores light field acquisition and processing, space-time light field rendering, and dynamic view synthesis with an array of cameras Because of the urgent challenges associated with emerging digital camera applications, image processing methods for computational photography are of paramount importance to research and development in the imaging community. Presenting the work of leading experts, and edited by a renowned authority in digital color imaging and camera image processing, this book considers the rapid developments in this area and addresses very particular research and application problems. It is ideal as a stand-alone professional reference for design and implementation of digital image and video processing tasks, and it can also be used to support graduate courses in computer vision, digital imaging, visual data processing, and computer graphics, among others.