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.

The 8-volume set, comprising the LNCS books 13801 until 13809, constitutes the refereed proceedings of 38 out of the 60 workshops held at the 17th European Conference on Computer Vision, ECCV 2022. The conference took place in Tel Aviv, Israel, during October 23-27, 2022; the workshops were held hybrid or online. The 367 full papers included in this volume set were carefully reviewed and selected for inclusion in the ECCV 2022 workshop proceedings. They were organized in individual parts as follows: Part I: W01 - AI for Space; W02 - Vision for Art; W03 - Adversarial Robustness in the Real World; W04 - Autonomous Vehicle Vision Part II: W05 - Learning With Limited and Imperfect Data; W06 - Advances in Image Manipulation; Part III: W07 - Medical Computer Vision; W08 - Computer Vision for Metaverse; W09 - Self-Supervised Learning: What Is Next?; Part IV: W10 - Self-Supervised Learning for Next-Generation Industry-Level Autonomous Driving; W11 - ISIC Skin Image Analysis; W12 - Cross-Modal Human-Robot Interaction; W13 - Text in Everything; W14 - BioImage Computing; W15 - Visual Object-Oriented Learning Meets Interaction: Discovery, Representations, and Applications; W16 - AI for Creative Video Editing and Understanding; W17 - Visual Inductive Priors for Data-Efficient Deep Learning; W18 - Mobile Intelligent Photography and Imaging; Part V: W19 - People Analysis: From Face, Body and Fashion to 3D Virtual Avatars; W20 - Safe Artificial Intelligence for Automated Driving; W21 - Real-World Surveillance: Applications and Challenges; W22 - Affective Behavior Analysis In-the-Wild; Part VI: W23 - Visual Perception for Navigation in Human Environments: The JackRabbot Human Body Pose Dataset and Benchmark; W24 - Distributed Smart Cameras; W25 - Causality in Vision; W26 - In-Vehicle Sensing and Monitorization; W27 - Assistive Computer Vision and Robotics; W28 - Computational Aspects of Deep Learning; Part VII: W29 - Computer Vision for Civil and Infrastructure Engineering; W30 - AI-Enabled Medical Image Analysis: Digital Pathology and Radiology/COVID19; W31 - Compositional and Multimodal Perception; Part VIII: W32 - Uncertainty Quantification for Computer Vision; W33 - Recovering 6D Object Pose; W34 - Drawings and Abstract Imagery: Representation and Analysis; W35 - Sign Language Understanding; W36 - A Challenge for Out-of-Distribution Generalization in Computer Vision; W37 - Vision With Biased or Scarce Data; W38 - Visual Object Tracking Challenge.

This textbook offers a statistical view on the geometry of multiple view analysis, required for camera calibration and orientation and for geometric scene reconstruction based on geometric image features. The authors have backgrounds in geodesy and also long experience with development and research in computer vision, and this is the first book to present a joint approach from the converging fields of photogrammetry and computer vision. Part I of the book provides an introduction to estimation theory, covering aspects such as Bayesian estimation, variance components, and sequential estimation, with a focus on the statistically sound diagnostics of estimation results essential in vision metrology. Part II provides tools for 2D and 3D geometric reasoning using projective geometry. This includes oriented projective geometry and tools for statistically optimal estimation and test of geometric entities and transformations and their relations, tools that are useful also in the context of uncertain reasoning in point clouds. Part III is devoted to modelling the geometry of single and multiple cameras, addressing calibration and orientation, including statistical evaluation and reconstruction of corresponding scene features and surfaces based on geometric image features. The authors provide algorithms for various geometric computation problems in vision metrology, together with mathematical justifications and statistical analysis, thus enabling thorough evaluations. The chapters are self-contained with numerous figures and exercises, and they are supported by an appendix that explains the basic mathematical notation and a detailed index. The book can serve as the basis for undergraduate and graduate courses in photogrammetry, computer vision, and computer graphics. It is also appropriate for researchers, engineers, and software developers in the photogrammetry and GIS industries, particularly those engaged with statistically based geometric computer vision methods.

The methodological book ""Laboratory techniques in cellular and molecular medicine"" is intended for students of bachelor, master, and doctoral study programmes at faculties of science, medicine, and veterinary medicine, as well as for laboratory technicians interested in methodological approaches of contemporary cellular and molecular medicine. The book does not aim to provide a comprehensive overview of the current state of the art in cellular and molecular medicine, that would be a superhuman task. The aim of the 56-member author team is to provide readers with an overview of the methods established and tested at the Institute of Molecular and Translational Medicine of the Faculty of Medicine of Palacký University Olomouc – to describe the methodological principles and their practical application. It focuses both on basic methods, whose principles are used by the most modern methods, and on special methods, reflecting the laboratory experience and specialisation of individual authors. The 52 chapters describe the work with cells and microorganisms, bioengineering manipulations of nucleic acids, the search for biomarkers, detection at the level of DNA, RNA, protein, organelle, and whole cell, and the use of fluorescent and radioactive labeling. To aid comprehension, the description of the methods is illustrated by figures and diagrams. Each chapter is followed by troubleshooting tips. The book promotes the best laboratory practice to increase the reproducibility of results in biomedicine.