The image taken by a moving camera changes with time. These image motions contain information about the motion of the camera and about the shapes of the objects in the field of view. There are two main types of image motion, finite displacements and image velocities. Finite displacements are described by the point correspondences between two images of the same scene taken from different positions. Image velocities are the velocities of the points in the image as they move over the projection surface. Reconstruction is the task of obtaining from the image-motions information about the camera motion or about the shapes of objects in the field of view. In this book the theory underlying reconstruction is described. Reconstruction from image motion is the subject matter of two different sci entific disciplines, photogrammetry and computer vision. In photogrammetry the accuracy of reconstruction is emphasised; in computer vision the emphasis is on methods for obtaining information from images in real time in order to guide a mechanical device such as a robot arm or an automatic vehicle. This book arises from recent work carried out in computer vision. Computer vision is a young field but it is developing rapidly. The earliest papers on reconstruction in the computer vision literature date back only to the mid 1970s. As computer vision develops, the mathematical techniques applied to the analysis of recon struction become more appropriate and more powerful.

"Analyzing a variety of films, video pieces, and performances, Sven Lütticken evaluates the impact that our changing experience of time has had on the actualization of history in the present."--Page 4 of cover.

"Explore the elements of composition, light, and direction that effectively create the illusion of time and motion in a digital image." The author explains how best to create these illusions and guides you through simple yet effective shooting techniques and post processing strategies.--[back cover].

Motion and Structure from Image Sequences is invaluable reading for researchers, graduate students, and practicing engineers dealing with computer vision. It presents a balanced treatment of the theoretical and practical issues, including very recent results - some of which are published here for the first time. The topics covered in detail are: - image matching and optical flow computation - structure from stereo - structure from motion - motion estimation - integration of multiple views - motion modeling and prediction Aspects such as uniqueness of the solution, degeneracy conditions, error analysis, stability, optimality, and robustness are also investigated. These details together with the fact that the algorithms are accessible without necessarily studying the rest of the material, make this book particularly attractive to practitioners.

Conducting the first comprehensive study of films that do not move, Justin Remes challenges the primacy of motion in cinema and tests the theoretical limits of film aesthetics and representation. Reading experimental films such as Andy Warhol's Empire (1964), the Fluxus work Disappearing Music for Face (1965), Michael Snow's So Is This (1982), and Derek Jarman's Blue (1993), he shows how motionless films defiantly showcase the static while collapsing the boundaries between cinema, photography, painting, and literature. Analyzing four categories of static film--furniture films, designed to be viewed partially or distractedly; protracted films, which use extremely slow motion to impress stasis; textual films, which foreground the static display of letters and written words; and monochrome films, which display a field of monochrome color as their image--Remes maps the interrelations between movement, stillness, and duration and their complication of cinema's conventional function and effects. Arguing all films unfold in time, he suggests duration is more fundamental to cinema than motion, initiating fresh inquiries into film's manipulation of temporality, from rigidly structured works to those with more ambiguous and open-ended frameworks. Remes's discussion integrates the writings of Roland Barthes, Gilles Deleuze, Tom Gunning, Rudolf Arnheim, Raymond Bellour, and Noel Carroll and will appeal to students of film theory, experimental cinema, intermedia studies, and aesthetics.

In 1872 an Englishman called Edward Muybridge photographed a horse in California and thereby invented the essentials of motion picture technology. His patron wanted to know if the horse ever lifted all four hooves at once. This is the story of Muybridge and modern technology.

An image or video sequence is a series of two-dimensional (2-D) images sequen tially ordered in time. Image sequences can be acquired, for instance, by video, motion picture, X-ray, or acoustic cameras, or they can be synthetically gen erated by sequentially ordering 2-D still images as in computer graphics and animation. The use of image sequences in areas such as entertainment, visual communications, multimedia, education, medicine, surveillance, remote control, and scientific research is constantly growing as the use of television and video systems are becoming more and more common. The boosted interest in digital video for both consumer and professional products, along with the availability of fast processors and memory at reasonable costs, has been a major driving force behind this growth. Before we elaborate on the two major terms that appear in the title of this book, namely motion analysis and image sequence processing, we like to place them in their proper contexts within the range of possible operations that involve image sequences. In this book, we choose to classify these operations into three major categories, namely (i) image sequence processing, (ii) image sequence analysis, and (iii) visualization. The interrelationship among these three categories is pictorially described in Figure 1 below in the form of an "image sequence triangle".

Human action analysis and recognition is a relatively mature field, yet one which is often not well understood by students and researchers. The large number of possible variations in human motion and appearance, camera viewpoint, and environment, present considerable challenges. Some important and common problems remain unsolved by the computer vision community. However, many valuable approaches have been proposed over the past decade, including the motion history image (MHI) method. This method has received significant attention, as it offers greater robustness and performance than other techniques. This work presents a comprehensive review of these state-of-the-art approaches and their applications, with a particular focus on the MHI method and its variants.

"Cinematic motion has long been celebrated as an emblem of change and fluidity or claimed as the source of cinema's impression of reality. But such general claims undermine the sheer variety of forms that motion can take onscreen-the sweep of a gesture, the rush of a camera movement, the slow transformations of a natural landscape. What might we learn about the moving image when we begin to account for the many ways that movements move? In The Shape of Motion: Cinema and the Aesthetics of Movement, Jordan Schonig provides a new way of theorizing cinematic motion by examining cinema's "motion forms:" structures, patterns, or shapes of movement unique to the moving image. From the wild and unpredictable motion of flickering leaves and swirling dust that captivated early spectators, to the pulsing abstractions that emerge from rapid lateral tracking shots, to the bleeding pixel-formations caused by the glitches of digital video compression, each motion form opens up the aesthetics of movement to film theoretical inquiry. By pairing close analyses of onscreen movement in narrative and experimental films with concepts from Maurice Merleau-Ponty, Henri Bergson, and Immanuel Kant, Schonig rethinks longstanding assumptions within film studies, such as indexical accounts of photographic images and analogies between the camera and the human eye. Arguing against the intuition that cinema reproduces our natural perception of motion, The Shape of Motion shows how cinema's motion forms do not merely transpose the movements of the world in front of the camera; they transform them"