Almost all museums hold photographs in their collections, and museum professionals and their audiences engage with photographs in a myriad of ways. Yet despite some three decades of critical museology and photographic theory, and an extensive debate on the politics of representation, outside art museums, almost no critical attention has been given specifically to the roles, purposes and lives of these photographs within museums. This book brings into focus the ubiquitous yet entirely unconsidered work that photographs are put to in museums. The authors' argument is that there is an economy of photographs in museums which is integral to the processes of the museum, and integral to the understanding of museums. The international contributors, drawn from curators and academics, reflect a range of visual and museological expertise. After an introduction setting out the range of questions and problems, the first part addresses broad curatorial strategies and ways of thinking about photographs in museums. Shifting the emphasis from curatorial practices and anxieties to the space of the gallery, this is followed by a series of case studies of exhibitionary practices and the museum strategies that support them. The third section focuses on the role of photographs in the museum articulation of ’difficult histories’. A final section addresses photograph collections in a digital environment. New technologies and new media have transformed the management, address and purposing in photographs in museums, from cataloguing practices to streaming on social media. These growing practices challenge both traditional hierarchies of knowledge in museums and the location of authority about photographs. The volume emerges from PhotoCLEC, a HERA funded project on museums and the photographic legacy of the colonial past in a postcolonial and multicultural Europe.

Citizens of networked societies are almost incessantly accompanied by ecologies of images. These ecologies of still and moving images present a paradox of uncertainties emerging along with certainties. Images appear more certain as the technical capacities that render them visible increase. At the same time, images are touched by more uncertainty as their numbers, manipulabilities, and contingencies multiply. With the emergence of big data, the image is becoming a dominant vehicle for the construction and presentation of the truth of data. Images present themselves as so many promises of the certainty, predictability, and intelligibility offered by data. The focus of this book is twofold. It analyses the kinds of images appearing today, showing how they are marked by a return to modern photographic emphases on high resolution, clarity, and realistic representation. Secondly, it discusses the ways in which the uncertainty of images is increasingly underscored within such reiterated emphases on allegedly certain visual truths. This often involves renewed encounters with noise, grain, glitch, blur, vagueness, and indistinctness. This book provides the reader with an intriguing transdisciplinary investigation of the uncertainly certain relation between the cultural imagination and the techno-aesthetic regime of big data and ubiquitous computing. This book was originally published as a special issue of Digital Creativity.

Almost all museums hold photographs in their collections, and museum professionals and their audiences engage with photographs in a myriad of ways. Yet despite some three decades of critical museology and photographic theory, and an extensive debate on the politics of representation, outside art museums, almost no critical attention has been given specifically to the roles, purposes and lives of these photographs within museums. This book brings into focus the ubiquitous yet entirely unconsidered work that photographs are put to in museums. The authors' argument is that there is an economy of photographs in museums which is integral to the processes of the museum, and integral to the understanding of museums. The international contributors, drawn from curators and academics, reflect a range of visual and museological expertise. After an introduction setting out the range of questions and problems, the first part addresses broad curatorial strategies and ways of thinking about photographs in museums. Shifting the emphasis from curatorial practices and anxieties to the space of the gallery, this is followed by a series of case studies of exhibitionary practices and the museum strategies that support them. The third section focuses on the role of photographs in the museum articulation of ’difficult histories’. A final section addresses photograph collections in a digital environment. New technologies and new media have transformed the management, address and purposing in photographs in museums, from cataloguing practices to streaming on social media. These growing practices challenge both traditional hierarchies of knowledge in museums and the location of authority about photographs. The volume emerges from PhotoCLEC, a HERA funded project on museums and the photographic legacy of the colonial past in a postcolonial and multicultural Europe.

Algebraic projective geometry, with its multilinear relations and its embedding into Grassmann-Cayley algebra, has become the basic representation of multiple view geometry, resulting in deep insights into the algebraic structure of geometric relations, as well as in efficient and versatile algorithms for computer vision and image analysis. This book provides a coherent integration of algebraic projective geometry and spatial reasoning under uncertainty with applications in computer vision. Beyond systematically introducing the theoretical foundations from geometry and statistics and clear rules for performing geometric reasoning under uncertainty, the author provides a collection of detailed algorithms. The book addresses researchers and advanced students interested in algebraic projective geometry for image analysis, in statistical representation of objects and transformations, or in generic tools for testing and estimating within the context of geometric multiple-view analysis.

In image processing and computer vision applications such as medical or scientific image data analysis, as well as in industrial scenarios, images are used as input measurement data. It is good scientific practice that proper measurements must be equipped with error and uncertainty estimates. For many applications, not only the measured values but also their errors and uncertainties, should be—and more and more frequently are—taken into account for further processing. This error and uncertainty propagation must be done for every processing step such that the final result comes with a reliable precision estimate. The goal of this book is to introduce the reader to the recent advances from the field of uncertainty quantification and error propagation for computer vision, image processing, and image analysis that are based on partial differential equations (PDEs). It presents a concept with which error propagation and sensitivity analysis can be formulated with a set of basic operations. The approach discussed in this book has the potential for application in all areas of quantitative computer vision, image processing, and image analysis. In particular, it might help medical imaging finally become a scientific discipline that is characterized by the classical paradigms of observation, measurement, and error awareness. This book is comprised of eight chapters. After an introduction to the goals of the book (Chapter 1), we present a brief review of PDEs and their numerical treatment (Chapter 2), PDE-based image processing (Chapter 3), and the numerics of stochastic PDEs (Chapter 4). We then proceed to define the concept of stochastic images (Chapter 5), describe how to accomplish image processing and computer vision with stochastic images (Chapter 6), and demonstrate the use of these principles for accomplishing sensitivity analysis (Chapter 7). Chapter 8 concludes the book and highlights new research topics for the future.

Scholars from a range of disciplines interrogate terms relevant to critical studies of big data, from abuse and aggregate to visualization and vulnerability. This pathbreaking work offers an interdisciplinary perspective on big data, interrogating key terms. Scholars from a range of disciplines interrogate concepts relevant to critical studies of big data--arranged glossary style, from from abuse and aggregate to visualization and vulnerability--both challenging conventional usage of such often-used terms as prediction and objectivity and introducing such unfamiliar ones as overfitting and copynorm. The contributors include both leading researchers, including N. Katherine Hayles, Johanna Drucker and Lisa Gitelman, and such emerging agenda-setting scholars as Safiya Noble, Sarah T. Roberts and Nicole Starosielski.

What’s the best way to develop for a Web gone wild? That’s easy. Simply scrap the rules you’ve relied on all these years and embrace uncertainty as a core tenet of design. In this practical book, veteran developer Rob Larsen outlines the principles out what he calls The Uncertain Web, and shows you techniques necessary to successfully make the transition. By combining web standards, progressive enhancement, an iterative approach to design and development, and a desire to question the status quo, your team can create sites and applications that will perform well in a wide range of present and future devices. This guide points the way. Topics include: Navigating thousands of browser/device/OS combinations Focusing on optimal, not absolute solutions Feature detection, Modernizr, and polyfills RWD, mobile first, and progressive enhancement UIs that work with multiple user input modes Image optimization, SVG, and server-side options The horribly complex world of web video The Web we want to see in the future