Feature-based Mini Unmanned Air Vehicle Video Euclidean Stabilization with Local Mosaics

154 Pages·2017·5.66 MB·English

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Theses and Dissertations
2007-02-01
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Damon Dyck Gerhardt
Brigham Young University - Provo
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Gerhardt, Damon Dyck, "Feature-based Mini Unmanned Air Vehicle Video Euclidean Stabilization with
Local Mosaics" (2007). Theses and Dissertations. 1056.
https://scholarsarchive.byu.edu/etd/1056
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FEATURE-BASED MINI UNMANNED AIR VEHICLE VIDEO
EUCLIDEAN STABILIZATION WITH LOCAL MOSAICS
by
Damon Gerhardt
A thesis submitted to the faculty of
Brigham Young University
in partial fulfillment of the requirements for the degree of
Master of Science
Department of Computer Science
Brigham Young University
April 2007
Copyright (cid:13)c 2007 Damon Gerhardt
All Rights Reserved
BRIGHAM YOUNG UNIVERSITY
GRADUATE COMMITTEE APPROVAL
of a thesis submitted by
Damon Gerhardt
This thesis has been read by each member of the following graduate committee and
by majority vote has been found to be satisfactory.
Date Bryan S. Morse, Chair
Date Michael A. Goodrich
Date Parris K. Egbert
BRIGHAM YOUNG UNIVERSITY
As chair of the candidate’s graduate committee, I have read the thesis of Damon
Gerhardt in its final form and have found that (1) its format, citations, and bibli-
ographical style are consistent and acceptable and fulfill university and department
style requirements; (2) its illustrative materials including figures, tables, and charts
are in place; and (3) the final manuscript is satisfactory to the graduate committee
and is ready for submission to the university library.
Date Bryan S. Morse
Chair, Graduate Committee
Accepted for the
Department Parris K. Egbert
Graduate Coordinator
Accepted for the
College Thomas W. Sederberg
AssociateDean, CollegeofPhysicalandMathematical
Sciences
ABSTRACT
FEATURE-BASED MINI UNMANNED AIR VEHICLE VIDEO
EUCLIDEAN STABILIZATION WITH LOCAL MOSAICS
Damon Gerhardt
Department of Computer Science
Master of Science
Video acquired using a camera mounted on a mini Unmanned Air Vehicle
(mUAV) may be very helpful in Wilderness Search and Rescue and many other ap-
plications but is commonly plagued with limited spatial and temporal field of views,
distractive jittery motions, disorienting rotations, and noisy and distorted images.
These problems collectively make it very difficult for human viewers to identify ob-
jects of interest as well as infer correct orientations throughout the video.
In order to expand the temporal and spatial field of view, stabilize, and better
orient users of noisy and distorted mUAV video, a method is proposed of estimating
in software and in real time the relative motions of each frame to the next by tracking
a small subset of features within each frame to the next. Using these relative motions,
a local Euclidean mosaic of the video can be created and a curve can be fit to the
video’s accumulative motion path to stabilize the presentations of both the video and
the local Euclidean mosaic.
The increase in users’ abilities to perform common search-and-rescue tasks of
identifying objects of interest throughout the stabilized and locally mosaiced mUAV
video is then evaluated. Finally, a discussion of remaining limitations is presented
along with some possibilities for future work.
ACKNOWLEDGMENTS
In behalf of my wife, my children, and my whole family, I am sincerely grateful
to Dr. Bryan Morse for his unwavering support, understanding, time, suggestions,
direction, and encouragement that he has dedicated to me to enter and complete
graduate school. Our lives are forever changed and improved because of him and his
many sacrifices for us, and to him we owe an unpayable debt.
In addition, I owe many thanks to the following: God for everything, my
parents for their lifelong nurturing, my sisters for their cheerleading efforts, BYU
and its Computer Science Department for its leadership, challenges, and funding, my
father-in-lawandfamily-in-lawfortheirsupport, Dr.DouglasCampbellandDr.Mark
Clement for their graduate school inspirations, Dr. Bryan Morse and Dr. Michael
Goodrich for fathering this mUAV vision effort as well as Dr. Parris Egbert and Dr.
Bill Barrett for their advice, Cameron Engh for working with me from the beginning
and suggesting the novel idea of using curves to stabilize video, Dr. Kevin Steele and
Dave Cline for their many helpful discussions and suggestions, Nathan Rasmussen
for introducing me to applicable and useful OpenCV functionality, Josh Keeler for
good lab laughs, Doug Kennard for being interested, the BYU Magicc lab for making
the mUAVs fly, Joe Jackson, Morgan Quigley, and Stephen Cluff for providing useful
mUAVvideos, JosephCooperfortrustingmycodetoworkwithhis, ChrisMonsonfor
a great LATEX template, and Dr. Dennis Eggett for his invaluable statistical analysis
of our results. I also thank all of these for their invaluable friendships and support.
Most of all, under God, I dedicate my work and my life to my wonderful
wife, Christine, and to my two wonderful boys, Jarom and Talon, who have all been
so amazingly supportive and understanding to sacrifice their time with me for this
degree. Now I can finally be a real part of the family.
Contents
1 Introduction 1
1.1 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.2 Problem Description . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.3 Related Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
1.4 Contributions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
1.4.1 Stabilization and Euclidean Local Mosaic . . . . . . . . . . . . 4
1.4.2 User Interface and User Study . . . . . . . . . . . . . . . . . . 5
1.5 Thesis Outline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
2 Background and Related Work 7
2.1 Definition of Terms . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
2.2 Frame Registration . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
2.2.1 Projective Geometry . . . . . . . . . . . . . . . . . . . . . . . 9
2.2.2 Intrinsic Parameters . . . . . . . . . . . . . . . . . . . . . . . 11
2.2.3 Extrinsic Parameters . . . . . . . . . . . . . . . . . . . . . . . 13
2.2.4 The Projection . . . . . . . . . . . . . . . . . . . . . . . . . . 14
2.3 Related Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
2.3.1 Image Alignment . . . . . . . . . . . . . . . . . . . . . . . . . 15
2.3.2 Related Mosaicing Research . . . . . . . . . . . . . . . . . . . 17
2.3.3 Related Stabilization Research . . . . . . . . . . . . . . . . . . 19
2.3.4 Image Acquisition Platforms . . . . . . . . . . . . . . . . . . . 20
2.3.5 Related UAV Vision Research . . . . . . . . . . . . . . . . . . 21
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