8 Result(s)
within
Chapter
Yi-Tong Zhou
English
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Chapter
Conclusions and Future Research
Several artificial neural networks were presented and applied to computer vision problems such as static and motion stereo, computation of optical flow, and image restoration. To ensure quick convergence of th...
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Introduction
This book is concerned with develo** algorithms for some important computer vision problems, especially at a low-level using artificial neural networks. The task of low-level vision is to recover physical pr...
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Motion Stereo—Longitudinal Motion
Longitudinal motion stereo sinfers depth information from a forward or backward motion, and consequently is particularly useful in autonomous robot navigation applications. Most existing algorithms have some p...
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Computational Neural Networks
Research on neural network modeling has a long history. Neurobiologists have discovered individual nerve cells existing in the brain and learned how neurons carry information, transmit information, and respond...
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Motion Stereo—Lateral Motion
Motion stereo is a method for deriving depth information from either a moving camera or objects moving through a stationary three-dimensional environment. In accordance with the nature of motion, motion stereo...
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Computation of Optical Flow
Optical flow is the distribution of apparent velocities of moving brightness patterns in an image. Ideally the optical flow corresponds to the motion field, but this is not always true [Hor86]. It is common to...
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Static Stereo
Recovering depth is a central problem in three-dimensional perception. Static stereo is a primary means for recovering depth from two images taken from different viewpoints. As early as 1838, Sir Charles Wheat...
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Image Restoration
Restoration of a high quality image from a degraded recording is an important problem in early vision processing. Image usually refers to a two-dimensional light intensity function x(a, b). Since light intensity ...
