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Computer vision and Mathematica
Computing and Visualization in Science, 2002Computer vision algorithms are strongly based on advanced mathematical methods. Tools to efficiently develop new methods are increasingly based on computer algebra systems, such as Matlab, Maple and Mathematica. For rapid prototyping both symbolic as numerical capability is required.
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Computer vision for computer games
Proceedings of the Second International Conference on Automatic Face and Gesture Recognition, 2002The appeal of computer games may be enhanced by vision-based user inputs. The high speed and low cost requirements for near-term, mass-market game applications make system design challenging. The response time of the vision interface should be less than a video frame time and the interface should cost less than $50 U.S.
Kenichi Tanaka +3 more
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PROPAGATING COVARIANCE IN COMPUTER VISION
International Journal of Pattern Recognition and Artificial Intelligence, 1996This paper describes how to propagate approximately additive random perturbations through any kind of vision algorithm step in which the appropriate random perturbation model for the estimated quantity produced by the vision step is also an additive random perturbation.
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Discrete optimization in computer vision
Computer Vision and Image Understanding, 2008International ...
Paragios, Nikos, Ramin, Zabih
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CVGIP: Image Understanding, 1994
Abstract In this paper we address the problem of methodologies for computer vision. In the first part we will present a brief survey of the Marr paradigm, e.g., what David Marr called his philosophy. We will emphasize the sequence of hypotheses which progressively makes the scene recovery approach explicit as well as the limitations of this approach.
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Abstract In this paper we address the problem of methodologies for computer vision. In the first part we will present a brief survey of the Marr paradigm, e.g., what David Marr called his philosophy. We will emphasize the sequence of hypotheses which progressively makes the scene recovery approach explicit as well as the limitations of this approach.
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Computer vision for ambient intelligence
Journal of Ambient Intelligence and Smart Environments, 2011A natural way of conceptualizing ambient intelligence is by picturing an active environment with access to perceptual input, not via eyes and ears, but by their technological counterparts. Computer vision is an essential part of building context-aware environments that adapt and anticipate their human users by understanding their behavior.
A. A. Salah +3 more
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Computational vision and regularization theory
Nature, 1985Descriptions of physical properties of visible surfaces, such as their distance and the presence of edges, must be recovered from the primary image data. Computational vision aims to understand how such descriptions can be obtained from inherently ambiguous and noisy data.
Poggio, Tomaso +2 more
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Quaternions in Computer Vision and Robotics
1982Computer Science ...
Edward Pervin, Jon A. Webb
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1995
Publisher Summary This chapter provides an overview of computer vision. The chapter begins with defining digital image as an array of numbers called greyscales associated with an image. Each of the cells in a digital image is called a picture element or pixel. Usually the greyscales are interpreted in terms of brightness: pixels with large numbers are
Jeffrey Johnson, Philip Picton
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Publisher Summary This chapter provides an overview of computer vision. The chapter begins with defining digital image as an array of numbers called greyscales associated with an image. Each of the cells in a digital image is called a picture element or pixel. Usually the greyscales are interpreted in terms of brightness: pixels with large numbers are
Jeffrey Johnson, Philip Picton
openaire +2 more sources