|
|
|
|
RI | Publications | Local Spatial Frequency Analysis for Computer Vision
|
|
Text only version of this site
Local Spatial Frequency Analysis for Computer Vision
J. Krumm and S. Shafer
tech. report CMU-RI-TR-90-11, Robotics Institute, Carnegie Mellon University, May, 1990.
Jump to: Download | Abstract | Notes | Text Reference | BibTeX Reference
| Download [Help] |
Adobe portable document format (pdf) [1883 KB]
Copyright notice: This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. These works may not be reposted without the explicit permission of the copyright holder.
| Abstract |
A sense of vision is a prerequisite for a robot to function in an unstructured environment. However. real-world scenes contain many interacting phenomena that lead to complex images which are difficult to interpret automatically. Typical computer vision research proceeds by analyzing various effects in isolation (eg. shading, texture, stereo. defocus). usually on images devoid of realistic complicating factors. This leads to specialized algorithms which fail on real-world images. Part of this failure is due to the dichotomy of useful representations for these phenomena. Some effects are best described in the spatial domain, while others are more naturally expressed in frequency. In order to resolve this dichotomy, we present the combined space/frequency repmmtaiion which, for each point in an image, shows the spatial fresuencies at that point. Within this common representation, we develop a set of simple. natural theories describing phenomena such as texture, shape, aliasing and lens parameters. We show how these theories lead to algorithms for shape from texture and for dealiasing image data The space/frequency representation should be a key aid in untangling the complex interaction of phenomena in images, allowing automatic understanding of real-world scenes.
| Notes |
Grant ID: #F33615-86-C-5-38
Associated center: VASC
Associated lab/group: Calibrated Imaging Lab
Associated project: Spatial Frequency
| Text Reference |
J. Krumm and S. Shafer, Local Spatial Frequency Analysis for Computer Vision, tech. report CMU-RI-TR-90-11, Robotics Institute, Carnegie Mellon University, May, 1990.
| BibTeX Reference |
@techreport{Krumm_1990_223,
author = "John Krumm and Steven Shafer",
title = "Local Spatial Frequency Analysis for Computer Vision",
institution = "Robotics Institute, Carnegie Mellon University",
month = "May",
year = "1990",
number = "CMU-RI-TR-90-11",
address = "Pittsburgh, PA"
}