Recognizing the Stranger


Book Description

Recognizing the Stranger is the first monographic study of recognition scenes and motifs in the Gospel of John. The recognition type-scene (anagnōrisis) was a common feature in ancient drama and narrative, highly valued by Aristotle as a touching moment of truth, e.g., in Oedipus’ tragic self-discovery and Odysseus’ happy homecoming. The book offers a reconstruction of the conventions of the genre and argues that it is one of the most recurrent and significant literary forms in the Gospel. When portraying Jesus as the divine stranger from heaven, the Gospel employs and transforms the formal and ideological structures of the type-scene in order to show how Jesus’ true identity can be recognized behind the half-mask of his human appearance.




Representations and Techniques for 3D Object Recognition and Scene Interpretation


Book Description

One of the grand challenges of artificial intelligence is to enable computers to interpret 3D scenes and objects from imagery. This book organizes and introduces major concepts in 3D scene and object representation and inference from still images, with a focus on recent efforts to fuse models of geometry and perspective with statistical machine learning. The book is organized into three sections: (1) Interpretation of Physical Space; (2) Recognition of 3D Objects; and (3) Integrated 3D Scene Interpretation. The first discusses representations of spatial layout and techniques to interpret physical scenes from images. The second section introduces representations for 3D object categories that account for the intrinsically 3D nature of objects and provide robustness to change in viewpoints. The third section discusses strategies to unite inference of scene geometry and object pose and identity into a coherent scene interpretation. Each section broadly surveys important ideas from cognitive science and artificial intelligence research, organizes and discusses key concepts and techniques from recent work in computer vision, and describes a few sample approaches in detail. Newcomers to computer vision will benefit from introductions to basic concepts, such as single-view geometry and image classification, while experts and novices alike may find inspiration from the book's organization and discussion of the most recent ideas in 3D scene understanding and 3D object recognition. Specific topics include: mathematics of perspective geometry; visual elements of the physical scene, structural 3D scene representations; techniques and features for image and region categorization; historical perspective, computational models, and datasets and machine learning techniques for 3D object recognition; inferences of geometrical attributes of objects, such as size and pose; and probabilistic and feature-passing approaches for contextual reasoning about 3D objects and scenes. Table of Contents: Background on 3D Scene Models / Single-view Geometry / Modeling the Physical Scene / Categorizing Images and Regions / Examples of 3D Scene Interpretation / Background on 3D Recognition / Modeling 3D Objects / Recognizing and Understanding 3D Objects / Examples of 2D 1/2 Layout Models / Reasoning about Objects and Scenes / Cascades of Classifiers / Conclusion and Future Directions




Disguise and Recognition in the Odyssey


Book Description

Disguise and Recognition in the Odyssey reveals the significance of the Odyssey's plot, in particular the many scenes of recognition that make up the hero's homecoming and dramatize the cardinal values of Homeric society, an aristocratic culture organized around recognition in the broader senses of honor, privilege, status, and fame. Odysseus' identity is seen to be rooted in his family relations, geographical origins, control of property, participation in the social institutions of hospitality and marriage, past actions, and ongoing reputation. At the same time, Odysseus' dependence on the acknowledgement of others ensures attention to multiple viewpoints, which makes the Odyssey more than a simple celebration of one man's preeminence and accounts in part for the poem's vigorous afterlife. The theme of disguise, which relies on plausible lies, highlights the nature of belief and the power of falsehood and creates the mixture of realism and fantasy that gives the Odyssey its distinctive texture. The book contains a pioneering analysis of the role of Penelope and the questions of female agency and human limitation raised by the critical debate about when exactly she recognizes that Odysseus has come home.




Love and Providence


Book Description

Love and Providence provides the first study of the recognition scene in Greek "romantic" novels and its significance in the ancient literary tradition.




Computer Vision – ECCV 2012


Book Description

The seven-volume set comprising LNCS volumes 7572-7578 constitutes the refereed proceedings of the 12th European Conference on Computer Vision, ECCV 2012, held in Florence, Italy, in October 2012. The 408 revised papers presented were carefully reviewed and selected from 1437 submissions. The papers are organized in topical sections on geometry, 2D and 3D shapes, 3D reconstruction, visual recognition and classification, visual features and image matching, visual monitoring: action and activities, models, optimisation, learning, visual tracking and image registration, photometry: lighting and colour, and image segmentation.




Indoor Scene Recognition by 3-D Object Search


Book Description

This book focuses on enabling mobile robots to recognize scenes in indoor environments, in order to allow them to determine which actions are appropriate at which points in time. In concrete terms, future robots will have to solve the classification problem represented by scene recognition sufficiently well for them to act independently in human-centered environments. To achieve accurate yet versatile indoor scene recognition, the book presents a hierarchical data structure for scenes – the Implicit Shape Model trees. Further, it also provides training and recognition algorithms for these trees. In general, entire indoor scenes cannot be perceived from a single point of view. To address this problem the authors introduce Active Scene Recognition (ASR), a concept that embeds canonical scene recognition in a decision-making system that selects camera views for a mobile robot to drive to so that it can find objects not yet localized. The authors formalize the automatic selection of camera views as a Next-Best-View (NBV) problem to which they contribute an algorithmic solution, which focuses on realistic problem modeling while maintaining its computational efficiency. Lastly, the book introduces a method for predicting the poses of objects to be searched, establishing the otherwise missing link between scene recognition and NBV estimation.




Pattern Recognition


Book Description

'Part-detective story, part-cultural snapshot . . . all bound by Gibson's pin-sharp prose' Arena -------------- THE FIRST NOVEL IN THE BLUE ANT TRILIOGY - READ ZERO HISTORY AND SPOOK COUNTRY FOR MORE Cayce Pollard has a new job. She's been offered a special project: track down the makers of an addictive online film that's lighting up the internet. Hunting the source will take her to Tokyo and Moscow and put her in the sights of Japanese hackers and Russian Mafia. She's up against those who want to control the film, to own it - who figure breaking the law is just another business strategy. The kind of people who relish turning the hunter into the hunted . . . A gripping spy thriller by William Gibson, bestselling author of Neuromancer. Part prophesy, part satire, Pattern Recognition skewers the absurdity of modern life with the lightest and most engaging of touches. Readers of Neal Stephenson, Ray Bradbury and Iain M. Banks won't be able to put this book down. -------------- 'Fast, witty and cleverly politicized' Guardian 'A big novel, full of bold ideas . . . races along like an expert thriller' GQ 'Dangerously hip. Its dialogue and characterization will amaze you. A wonderfully detailed, reckless journey of espionage and lies' USA Today 'A compelling, humane story with a sympathetic heroine searching for meaning and consolation in a post-everything world' Daily Telegraph 'Electric, profound. Gibson's descriptions of Tokyo, Russia and London are surreally spot-on' Financial Times




Imaging Spectroscopy for Scene Analysis


Book Description

This book presents a detailed analysis of spectral imaging, describing how it can be used for the purposes of material identification, object recognition and scene understanding. The opportunities and challenges of combining spatial and spectral information are explored in depth, as are a wide range of applications. Features: discusses spectral image acquisition by hyperspectral cameras, and the process of spectral image formation; examines models of surface reflectance, the recovery of photometric invariants, and the estimation of the illuminant power spectrum from spectral imagery; describes spectrum representations for the interpolation of reflectance and radiance values, and the classification of spectra; reviews the use of imaging spectroscopy for material identification; explores the recovery of reflection geometry from image reflectance; investigates spectro-polarimetric imagery, and the recovery of object shape and material properties using polarimetric images captured from a single view.




Multimodal Scene Understanding


Book Description

Multimodal Scene Understanding: Algorithms, Applications and Deep Learning presents recent advances in multi-modal computing, with a focus on computer vision and photogrammetry. It provides the latest algorithms and applications that involve combining multiple sources of information and describes the role and approaches of multi-sensory data and multi-modal deep learning. The book is ideal for researchers from the fields of computer vision, remote sensing, robotics, and photogrammetry, thus helping foster interdisciplinary interaction and collaboration between these realms. Researchers collecting and analyzing multi-sensory data collections – for example, KITTI benchmark (stereo+laser) - from different platforms, such as autonomous vehicles, surveillance cameras, UAVs, planes and satellites will find this book to be very useful. - Contains state-of-the-art developments on multi-modal computing - Shines a focus on algorithms and applications - Presents novel deep learning topics on multi-sensor fusion and multi-modal deep learning




Scene Vision


Book Description

Cutting-edge research on the visual cognition of scenes, covering issues that include spatial vision, context, emotion, attention, memory, and neural mechanisms underlying scene representation. For many years, researchers have studied visual recognition with objects—single, clean, clear, and isolated objects, presented to subjects at the center of the screen. In our real environment, however, objects do not appear so neatly. Our visual world is a stimulating scenery mess; fragments, colors, occlusions, motions, eye movements, context, and distraction all affect perception. In this volume, pioneering researchers address the visual cognition of scenes from neuroimaging, psychology, modeling, electrophysiology, and computer vision perspectives. Building on past research—and accepting the challenge of applying what we have learned from the study of object recognition to the visual cognition of scenes—these leading scholars consider issues of spatial vision, context, rapid perception, emotion, attention, memory, and the neural mechanisms underlying scene representation. Taken together, their contributions offer a snapshot of our current knowledge of how we understand scenes and the visual world around us. Contributors Elissa M. Aminoff, Moshe Bar, Margaret Bradley, Daniel I. Brooks, Marvin M. Chun, Ritendra Datta, Russell A. Epstein, Michèle Fabre-Thorpe, Elena Fedorovskaya, Jack L. Gallant, Helene Intraub, Dhiraj Joshi, Kestutis Kveraga, Peter J. Lang, Jia Li Xin Lu, Jiebo Luo, Quang-Tuan Luong, George L. Malcolm, Shahin Nasr, Soojin Park, Mary C. Potter, Reza Rajimehr, Dean Sabatinelli, Philippe G. Schyns, David L. Sheinberg, Heida Maria Sigurdardottir, Dustin Stansbury, Simon Thorpe, Roger Tootell, James Z. Wang