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Differential techniques for the accurate estimation of image flow

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Bainbridge-Smith, Andrew S. L (1996) Differential techniques for the accurate estimation of image flow. PhD thesis, University of Tasmania.

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Abstract

One of the prime objectives of many robotic systems is the ability to judge depth for self
navigation. This depth or range information in a three-dimensional scene has traditionally
been obtained from point correspondences in static two-dimensional images, a process often
known as photogrammetry. This approach has the major difficulty that point pairs corresponding
to a common three-dimensional scene point are not easy to identify automatically
in images. In more recent years a wide range of alternative approaches for estimating depth
have emerged. One such group of techniques makes use of multiple images from a single
moving sensor. Known as shape from motion algorithms, they often employ a three step
process to estimating depth. The first step involves estimating the optical or image flow.
The second step then estimates the global motion parameters of the image sensor from
the image flow. The final step involves estimating the relative depth from the image flow
and motion parameters. Thus in order to make reliable depth estimates, accurate image
flow measures are required. This thesis, therefore, concentrates on the detailed analysis of
techniques employed for accurately determining image flow.
Preliminary chapters introduce basic computer vision concepts and image flow algorithms.
As some of the terminology used in this field is ambiguous, particular care has been placed
on presenting a well defined set of terms, notably defining: "camera motion", the "motion
field", "optical flow" and "image flow". Also defined is the "aperture problem" which
describes a fundamental inability to perceive or measure motion in directions were no change
in the image intensity function is present. It is demonstrated that all techniques rely on the
presence of non-zero second order differential terms of the image sensor intensity function
to overcome the aperture problem.
Following chapters present a review and comparison of a number of image flow techniques,
with particular emphasis placed on gradient methods. It is argued that the fundamental
problem of measuring image flow is to determine the velocity in as small an aperture as
possible. Based on this criteria it is concluded that the technique based on a weighted least
squares solution of first order differential terms of the image intensity is the best generalized
second order method for achieving this objective.
The practical issues of regularization of the gradient calculations and the influence of noise
corruption are investigated. Conclusions drawn show the importance of smoothing and the
effects of excessive smoothing, including a loss of spatial precision and an increase in numerical
error due to the computation of small gradient terms. Importantly it is demonstrated
that spatial and temporal gradients are not independent and consequentially their respective
errors are correlated. It is thus shown that many image flow estimation techniques
exhibit a systematic bias.
An investigation into methods of assessing the quality of image flow estimates is also made.
Indicators of the quality of an estimate are required in order to evaluate the accuracy of
subsequent estimates made from them; particularly depth estimates, segmentation of the
image flow field, and determining the optimal aperture size for making image flow estimates.
Findings illustrate that the correlation between many commonly used, or proposed,
indicators of image flow error are poor.
Some investigative work into two innovative approaches for estimating image flow, based on
the use of colour and actual camera motion parameters, is presented. It is shown that both
colour and camera motion parameters provide an additional constraint to the estimation
procedure, which can be used to improve the resolution of the image flow field by allowing
smaller apertures to be considered. Preliminary results from these studies suggest that both
sources of additional information improve the robustness of the algorithms.
The final part of this thesis presents some quantitative and qualitative results for image
flow estimates from real imagery. A summary of conclusions is presented and a number of
advanced issues and suggested extensions are outlined.

Item Type: Thesis (PhD)
Copyright Holders: The Author
Copyright Information:

Copyright 1996 the Author - The University is continuing to endeavour to trace the copyright
owner(s) and in the meantime this item has been reproduced here in good faith. We
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Additional Information:

Addresses the ability of robotic systems to judge depth for self navigation, concentrating on the detailed analysis of techniques employed for accurately determining image flow. Basic computer vision concepts and image flow algorithms are considered, and a number of image flow techniques are presented, with particular emphasis on gradient methods. Thesis (Ph.D.)--University of Tasmania, 1997. Includes bibliographical references. Addresses the ability of robotic systems to judge depth for self navigation, concentrating on the detailed analysis of techniques employed for accurately determining image flow. Basic computer vision concepts and image flow algorithms are considered, and a number of image flow techniques are presented, with particular emphasis on gradient methods

Date Deposited: 25 Nov 2014 00:46
Last Modified: 11 Mar 2016 05:55
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