Handbook of Mathematical Models in Computer Vision

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9780387263717: Handbook of Mathematical Models in Computer Vision

Abstract Biological vision is a rather fascinating domain of research. Scientists of various origins like biology, medicine, neurophysiology, engineering, math­ ematics, etc. aim to understand the processes leading to visual perception process and at reproducing such systems. Understanding the environment is most of the time done through visual perception which appears to be one of the most fundamental sensory abilities in humans and therefore a significant amount of research effort has been dedicated towards modelling and repro­ ducing human visual abilities. Mathematical methods play a central role in this endeavour. Introduction David Marr's theory v^as a pioneering step tov^ards understanding visual percep­ tion. In his view human vision was based on a complete surface reconstruction of the environment that was then used to address visual subtasks. This approach was proven to be insufficient by neuro-biologists and complementary ideas from statistical pattern recognition and artificial intelligence were introduced to bet­ ter address the visual perception problem. In this framework visual perception is represented by a set of actions and rules connecting these actions. The emerg­ ing concept of active vision consists of a selective visual perception paradigm that is basically equivalent to recovering from the environment the minimal piece information required to address a particular task of interest.

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Visual perception refers to the ability of understanding the visual information that is provided by the environment. Such a mechanism integrates several human abilities and was studied by many researchers with different scientific origins including philosophy, physiology, biology, neurobiology, mathematics and engineering. In particular in the recent years an effort to understand, formalize and finally reproduce mechanical visual perception systems able to see and understand the environment using computational theories was made by mathematicians, statisticians and engineers. Such a task connects visual tasks with optimization processes and the answer to the visual perception task corresponds to the lowest potential of a task-driven objective function. In this edited volume we present the most prominent mathematical models that are considered in computational vision. To this end, tasks of increasing complexity are considered and we present the state-of-the-art methods to cope with such tasks. The volume consists of six thematic areas that provide answers to the most dominant questions of computational vision:

Image reconstruction,

Segmentation and object extraction,

Shape modeling and registration,

Motion analysis and tracking,

3D from images, geometry and reconstruction

Applications in medical image analysis

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"The focus of the book is on mathematical methods that both model and reproduce human visual abilities. ... This book is a must-have for those interested in the full breadth of research done in the biological & computer vision community. As a bonus, the chapters can also be used in a seminar-based, advanced undergraduate course in mathematical based computer vision. " (Arjan Kuijper, IAPR Newsletter, October, 2006)

"Computational visual perception can be defined as the discipline of enabling computers to identify features in image data. ... I found this book to be detailed and comprehensive enough to be well worth the time spent on it. Citations linking the text to the relevant literature are profusely sprinkled throughout the text, and a very extensive bibliography is included ... . the production qualities are excellent. ... it should be a useful reference text for researchers or practitioners in this field." (R. M. Malyankar, Computing Reviews, January, 2006)

"The editors of this important compendium view their task as a contribution to modeling and simulating human vision by machine. ... The editors should be congratulated for bringing together high-level researchers to contribute chapters on cutting-edge technologies based on mathematical modeling. This compendium is a solid contribution to the recent literature combining the theories and applications of mathematical modeling to the domain of computer vision." (R. Goldberg, Computing Reviews, June, 2006)

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Book Description Springer-Verlag New York Inc., United States, 2005. Hardback. Book Condition: New. Language: English . Brand New Book. Abstract Biological vision is a rather fascinating domain of research. Scientists of various origins like biology, medicine, neurophysiology, engineering, math- ematics, etc. aim to understand the processes leading to visual perception process and at reproducing such systems. Understanding the environment is most of the time done through visual perception which appears to be one of the most fundamental sensory abilities in humans and therefore a significant amount of research effort has been dedicated towards modelling and repro- ducing human visual abilities. Mathematical methods play a central role in this endeavour. Introduction David Marr s theory v^as a pioneering step tov^ards understanding visual percep- tion. In his view human vision was based on a complete surface reconstruction of the environment that was then used to address visual subtasks. This approach was proven to be insufficient by neuro-biologists and complementary ideas from statistical pattern recognition and artificial intelligence were introduced to bet- ter address the visual perception problem. In this framework visual perception is represented by a set of actions and rules connecting these actions. The emerg- ing concept of active vision consists of a selective visual perception paradigm that is basically equivalent to recovering from the environment the minimal piece information required to address a particular task of interest. Bookseller Inventory # AAZ9780387263717

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Book Description Springer-Verlag New York Inc., United States, 2005. Hardback. Book Condition: New. Language: English . Brand New Book. Abstract Biological vision is a rather fascinating domain of research. Scientists of various origins like biology, medicine, neurophysiology, engineering, math- ematics, etc. aim to understand the processes leading to visual perception process and at reproducing such systems. Understanding the environment is most of the time done through visual perception which appears to be one of the most fundamental sensory abilities in humans and therefore a significant amount of research effort has been dedicated towards modelling and repro- ducing human visual abilities. Mathematical methods play a central role in this endeavour. Introduction David Marr s theory v^as a pioneering step tov^ards understanding visual percep- tion. In his view human vision was based on a complete surface reconstruction of the environment that was then used to address visual subtasks. This approach was proven to be insufficient by neuro-biologists and complementary ideas from statistical pattern recognition and artificial intelligence were introduced to bet- ter address the visual perception problem. In this framework visual perception is represented by a set of actions and rules connecting these actions. The emerg- ing concept of active vision consists of a selective visual perception paradigm that is basically equivalent to recovering from the environment the minimal piece information required to address a particular task of interest. Bookseller Inventory # AAZ9780387263717

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Book Description Springer-Verlag New York Inc. Hardback. Book Condition: new. BRAND NEW, The Handbook of Mathematical Models in Computer Vision, Nikos Paragios, Chen Yunmei, Olivier Faugeras, Abstract Biological vision is a rather fascinating domain of research. Scientists of various origins like biology, medicine, neurophysiology, engineering, math- ematics, etc. aim to understand the processes leading to visual perception process and at reproducing such systems. Understanding the environment is most of the time done through visual perception which appears to be one of the most fundamental sensory abilities in humans and therefore a significant amount of research effort has been dedicated towards modelling and repro- ducing human visual abilities. Mathematical methods play a central role in this endeavour. Introduction David Marr's theory v^as a pioneering step tov^ards understanding visual percep- tion. In his view human vision was based on a complete surface reconstruction of the environment that was then used to address visual subtasks. This approach was proven to be insufficient by neuro-biologists and complementary ideas from statistical pattern recognition and artificial intelligence were introduced to bet- ter address the visual perception problem. In this framework visual perception is represented by a set of actions and rules connecting these actions. The emerg- ing concept of active vision consists of a selective visual perception paradigm that is basically equivalent to recovering from the environment the minimal piece information required to address a particular task of interest. Bookseller Inventory # B9780387263717

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Book Description Springer, 2005. Book Condition: New. Provides a discourse on the mathematical models used in computational vision. This book includes topics such as image reconstruction, segmentation and object extraction, shape modeling and registration, motion analysis and tracking, and 3D from images, geometry and reconstruction. It also presents a study of applications in medical image analysis. Editor(s): Paragios, Nikos (Imaging and Visualization Department Siemens Corporate Research, Princeton, USA); Chen Yunmei; Faugeras, Olivier. Num Pages: 606 pages, biography. BIC Classification: PBWH; UGK. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly; (UU) Undergraduate. Dimension: 244 x 167 x 42. Weight in Grams: 1056. . 2005. 2006th Edition. Hardcover. . . . . . Bookseller Inventory # V9780387263717

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Book Description Springer. Book Condition: New. Provides a discourse on the mathematical models used in computational vision. This book includes topics such as image reconstruction, segmentation and object extraction, shape modeling and registration, motion analysis and tracking, and 3D from images, geometry and reconstruction. It also presents a study of applications in medical image analysis. Editor(s): Paragios, Nikos (Imaging and Visualization Department Siemens Corporate Research, Princeton, USA); Chen Yunmei; Faugeras, Olivier. Num Pages: 606 pages, biography. BIC Classification: PBWH; UGK. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly; (UU) Undergraduate. Dimension: 244 x 167 x 42. Weight in Grams: 1056. . 2005. 2006th Edition. Hardcover. . . . . Books ship from the US and Ireland. Bookseller Inventory # V9780387263717

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