Fourier Vision: Segmentation and Velocity Measurement using the Fourier Transform

Overview

Fourier Vision provides a new treatment of figure-ground segmentation in scenes comprising transparent, translucent, or opaque objects. Exploiting the relative motion between figure and ground, this technique deals explicitly with the separation of additive signals and makes no assumptions about the spatial or spectral content of the images, with segmentation being carried out phasor by phasor in the Fourier domain. It works with several camera configurations, such as camera motion and short-baseline binocular ...
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Overview

Fourier Vision provides a new treatment of figure-ground segmentation in scenes comprising transparent, translucent, or opaque objects. Exploiting the relative motion between figure and ground, this technique deals explicitly with the separation of additive signals and makes no assumptions about the spatial or spectral content of the images, with segmentation being carried out phasor by phasor in the Fourier domain. It works with several camera configurations, such as camera motion and short-baseline binocular stereo, and performs best on images with small velocities/displacements, typically one to ten pixels per frame. The book also addresses the use of Fourier techniques to estimate stereo disparity and optical flow. Numerous examples are provided throughout.
Fourier Vision will be of value to researchers in image processing & computer vision and, especially, to those who have to deal with superimposed transparent or translucent objects. Researchers in application areas such as medical imaging and acoustic signal processing will also find this of interest.
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Editorial Reviews

From The Critics
Fourier and Hough transforms are described in this text as an approach to deal with issues of separation of additive images and segmentation of figure-ground scenes. Vernon (National U. of Ireland, Maynooth) describes the math used in the process then discusses monocular and binocular vision and instantaneous and decoupled optical flow. The text will be of interest to those working with image processing and computer vision, especially when dealing with superimposed transparent or translucent objects. No assumptions are made about the spatial or spectral content of the images; segmentation is carried out phasor by phasor in the Fourier domain. Annotation c. Book News, Inc., Portland, OR (booknews.com)
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Product Details

Table of Contents

Preface. 1. Introduction. 2. Mathematical Preliminaries. 3. Monocular Vision - Segmentation in Additive Images. 4. Monocular Vision - Segmentation in Occluding Images. 5. Articulated Binocular Vision. 6. Fronto-Parallel Binocular Vision. 7. Instantaneous Optical Flow. 8. Decoupled Optical Flow. 9. Epilogue.
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