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A wealth of advanced pattern recognition algorithms are emerging from the interdiscipline between technologies of effective visual features and the human-brain cognition process. Effective visual features are made possible through the rapid developments in appropriate sensor equipments, novel filter designs, and viable information processing architectures. While the understanding of human-brain cognition process broadens the way in which the computer can perform pattern recognition tasks. The present book is intended to collect representative researches around the globe focusing on low-level vision, filter design, features and image descriptors, data mining and analysis, and biologically inspired algorithms. The 27 chapters coved in this book disclose recent advances and new ideas in promoting the techniques, technology and applications of pattern recognition.

Pattern perception. --- Pattern recognition systems. --- Pattern classification systems --- Pattern recognition computers --- Pattern perception --- Computer vision --- Design perception --- Pattern recognition --- Form perception --- Perception --- Figure-ground perception --- Machine learning

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"Visual Reconstruction presents a unified and highly original approach to the treatment of continuity in vision. It introduces, analyzes, and illustrates two new concepts. The first -- the weak continuity constraint -- is a concise, computational formalization of piecewise continuity. It is a mechanism for expressing the expectation that visual quantities such as intensity, surface color, and surface depth vary continuously almost everywhere, but with occasional abrupt changes. The second concept -- the graduated nonconvexity algorithm -- arises naturally from the first. It is an efficient, deterministic (nonrandom) algorithm for fitting piecewise continuous functions to visual data. The book first illustrates the breadth of application of reconstruction processes in vision with results that the authors' theory and program yield for a variety of problems. The mathematics of weak continuity and the graduated nonconvexity (GNC) algorithm are then developed carefully and progressively."

Pattern perception --- #TELE:MI2 --- Design perception --- Pattern recognition --- Form perception --- Perception --- Figure-ground perception --- Pattern perception. --- Engineering & Applied Sciences --- Computer Science --- NEUROSCIENCE/Visual Neuroscience --- COMPUTER SCIENCE/Artificial Intelligence

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A novel treatment of the capacity for shared attention, joint action, and perceptual common knowledge. In The Shared World, Axel Seemann offers a new treatment of the capacity to perceive, act on, and know about the world together with others. Seemann argues that creatures capable of joint attention stand in a unique perceptual and epistemic relation to their surroundings; they operate in an environment that they, through their communication with their fellow perceivers, help constitute. Seemann shows that this relation can be marshaled to address a range of questions about the social aspect of the mind and its perceptual and cognitive capacities. Seemann begins with a conceptual question about a complex kind of sociocognitive phenomenon--perceptual common knowledge--and develops an empirically informed account of the spatial structure of the environment in and about which such knowledge is possible. In the course of his argument, he addresses such topics as demonstrative reference in communication, common knowledge about jointly perceived objects, and spatial awareness in joint perception and action.

Political philosophy. Social philosophy --- Social psychology --- Perception (Philosophy) --- Communication --- Space perception --- Social aspects. --- Spatial perception --- Perception --- Spatial behavior --- Figure-ground perception --- Geographical perception --- Communication and culture --- Philosophy

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Space perception --- Visual perception --- Spatial perception --- Optics, Psychological --- Vision --- Psychological aspects --- Affective and dynamic functions --- Perception --- Spatial behavior --- Figure-ground perception --- Geographical perception --- Visual discrimination

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This book provides a fundamentally new approach to pattern recognition in which objects are characterized by relations to other objects instead of by using features or models. This 'dissimilarity representation' bridges the gap between the traditionally opposing approaches of statistical and structural pattern recognition. Physical phenomena, objects and events in the world are related in various and often complex ways. Such relations are usually modeled in the form of graphs or diagrams. While this is useful for communication between experts, such representation is difficult to combine and in

Pattern perception. --- Pattern recognition systems. --- Pattern classification systems --- Pattern recognition computers --- Pattern perception --- Computer vision --- Design perception --- Pattern recognition --- Form perception --- Perception --- Figure-ground perception