Hand Tracking, Finger Identification, and Chordic Manipulation on

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Approved: Approved: Approved: HAND TRACKING, FINGER IDENTIFICATION, AND CHORDIC MANIPULATION ON A MULTI-TOUCH SURFACE by Wayne Westerman Neal Gallagher, Ph.D. Chair of the Department of Electrical Engineering Andras Z. Szeri, Ph.D. Interim Dean of the College of Engineering John C. Cavanaugh, Ph.D. Vice Provost for Academic Programs <strong>and</strong> Planning
Signed: Signed: Signed: Signed: Signed: I certify that I have read this dissertation <strong>and</strong> that in my opinion it meets the academic <strong>and</strong> professional st<strong>and</strong>ard required by the University as a dissertation for the degree of Doctor of Philosophy. John Elias, Ph.D. Professor in charge of dissertation I certify that I have read this dissertation <strong>and</strong> that in my opinion it meets the academic <strong>and</strong> professional st<strong>and</strong>ard required by the University as a dissertation for the degree of Doctor of Philosophy. Charles Boncelet, Ph.D. Member of dissertation committee I certify that I have read this dissertation <strong>and</strong> that in my opinion it meets the academic <strong>and</strong> professional st<strong>and</strong>ard required by the University as a dissertation for the degree of Doctor of Philosophy. Phillip Christie, Ph.D. Member of dissertation committee I certify that I have read this dissertation <strong>and</strong> that in my opinion it meets the academic <strong>and</strong> professional st<strong>and</strong>ard required by the University as a dissertation for the degree of Doctor of Philosophy. Kenneth Barner, Ph.D. Member of dissertation committee I certify that I have read this dissertation <strong>and</strong> that in my opinion it meets the academic <strong>and</strong> professional st<strong>and</strong>ard required by the University as a dissertation for the degree of Doctor of Philosophy. John Scholz, Ph.D. Member of dissertation committee
Page 1: HAND TRACKING, FINGER IDENTIFICATIO
Page 5 and 6: Samuel Audet, for generously writin
Page 7 and 8: 1.5 What is Not Covered : : : : : :
Page 9 and 10: 3.3.2 Prediction of Contact Locatio
Page 11 and 12: 4.5.4 The Optimization Search Loop
Page 13 and 14: CONCLUSIONS : : : : : : : : : : : :
Page 15 and 16: LIST OF FIGURES 1.1 Warped QWERTY k
Page 17 and 18: 3.8 The correct segmentation for th
Page 19 and 20: 4.12 Identity swaps which occurs af
Page 21 and 22: 4.39 Palm cohesion factor versus th
Page 23 and 24: LIST OF TABLES 1.1 Legend for nger
Page 25 and 26: cubital tunnel syndrome Same as car
Page 27 and 28: path In context of Chapters 3{5, th
Page 29 and 30: ABSTRACT This research introduces m
Page 31 and 32: Chapter 1 INTRODUCTION 1.1 The Stat
Page 33 and 34: volume of computer programming for
Page 35 and 36: esponsiveness of the controls on a
Page 37 and 38: without indentations to force the n
Page 39 and 40: Table 1.1: Legend for nger combinat
Page 41 and 42: Tapping these two ngers simultaneou
Page 43 and 44: two nger chord moves the text curso
Page 45 and 46: The proximity sensors measure the e
Page 47 and 48: TYPING RECOGNIZER FINGER SYNCHRONIZ
Page 49 and 50: hand position esti
Page 51 and 52: extract independent translation, sc
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the nger synchronization detector w
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very important preventive measures
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1.6.2.5 Minimize user anticipation
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extracted from hand</strong
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language as they appear in communic
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2.1.5 Sensing Finger</stron
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a) b) c) d) Figure 2.2: Projection
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a) b) c) d) Figure 2.3: Ambiguities
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few millimeters of the electrodes.
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41 Vertical Position on Surface (Y
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2.1.9 No Motion Blur on MTS Another
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position is indicated by the amount
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The o set-corrected image E is then
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touches the surface and</st
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2.3.2 Properties of H<stron
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Vertical Position on Surface (Y axi
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PATHS FROM PREVIOUS IMAGES HAND IDE
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3.2 Contact Segmentation The object
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CURRENT PROXIMITY IMAGE DIFFUSE CUR
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proximity signal Gz, orientation G
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guessed at. Since strict segmentati
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hand position at l
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A) B) Figure 3.4: Typical search pa
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with excluded electrodes in between
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threshold Kmaxima significance. Usi
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or Si�j[n]
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etween palm heels can be measured.
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3.2.8 Extracting Group Parameters T
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For convenience while distinguishin
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Note that usually each palm heel wi
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groups. Comparing the size of the p
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any alignment within a couple centi
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a) b) Figure 3.10: Unsmoothed a) <s
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a) b) Figure 3.12: Unsmoothed a) <s
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it can get to the index ngertip <st
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444 444 11 444 1111 222 33 44 1111
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STRICT SEGMENTATION REGION 22 111 2
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STRICT SEGMENTATION REGION 111 222
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or hand resting. T
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pairing method for marginal cases d
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Ppredy[n] = Py[n ; 1] + 4tPvy[n ; 1
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Pz[n] = Gz (3.36) P [n] = G (3.37)
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of that contact's path by the path
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problem which must optimally match
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channels can still be reserved for
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to impose an ordering relation betw
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eliably identify all of a h
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or default hand po
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PATHS FROM PREVIOUS IMAGES HAND IDE
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when a hand is not
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4.3.1 Measuring Current H<s
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hand o set (Hmox[n
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eturns to default position. Alterna
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the estimated left hand</st
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START DEFINE IDENTITY ATTRACTORS AT
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Vertical Surface Position (cm) 12 1
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The optimization can then be stated
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solution techniques should be e cie
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4.4.4.4 The k-exchange Sequence The
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Pg o Pg o D D x x x x g' a Ab g' Aa
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g o h' x x a g' b g o h' x x a g' b
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This simple condition ensures that
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4.4.5.3 Summary of Swapping Behavio
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= jj ~agjj 4 +2jj ~agjj 2 jj ~ bhjj
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fairly gradual. Though the unsquare
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constrain one another within the ar
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A1 x F1 o A7 x x A2 D F2 o A3 x o A
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inter-contact angles in the same wa
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hand contact will
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With these weighted palm heel attra
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Vertical Position on Surface (cm) 1
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experimenter then adjusts the ampli
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4.4.6.6 Palm Heel Size Factor Palm
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palm separation factor quickly decr
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where cij is the weighted distance
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are compiled. These statistics prov
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183 pinch gesture, the thumb may st
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it would erroneously grow in respon
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Like the Voronoi cells of the assig
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shifting of assignments for h<stron
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ecently lifted o nearby also proves
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surface a few dozen milliseconds af
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Vertical Surface Position (cm) 12 1
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processes can execute using the act
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can, creating an ambiguity inwhich
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213 is present or if the cluster sl
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(Figures 4.43, 4.44). Since thumb o
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Chapter 5 CHORDIC MANIPULATION This
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task of moving the hand</st
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1990s with credit-card-sized touchp
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approach could only track the nger
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graphical manipulation tasks. Such
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e suppressed so that control occurs
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stretchable squares, bricks, or rot
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hand part touches
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GET HAND'S CURRENT PATH PARAMETERS
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ngers which lift o at about the sam
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Note that nger pair synchronization
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for examples of other chord tap eve
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the path is found to be a member of
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of the proximity pro le is measured
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The purpose of the motion component
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START GET HAND'S CURRENT PATH PARAM
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the di erence between motion of a c
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motion or control to display gain t
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ut produces output speeds in propor
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the nger-weighted translation compo
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Horiz. Trans. Velocity (m/s) Vert.
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5.4.1.1 Channels Follow Fin
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operators can set the thumb down sh
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threshold will be crossed until nge
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Table 5.2: The simple manipulations
Page 305 and 306:
5.5 Conclusions This chapter has de
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6.1.1 My Fitness as an Evaluator As
Page 309 and 310:
This dissertation was written in th
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6.1.4 Weekly Symptoms 6.1.4.1 First
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283 Figure 6.1: Modi ed Dvorak key
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6.1.5 Recognition Errors an
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taps or stringently adapting deboun
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Right Hand
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Right Hand
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either hand, <stro
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Table 6.5: Schedule for MTS usabili
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Subjects would continue to use thei
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during this session while subjects
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6.3.3 Universal Access People with
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systems allow more than one pointin
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Appendix A ERGONOMICS FOR ENGINEERS
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example, extreme wrist exion or ext
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and an increase in
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a) b) c) d) e) f) g) Figure B.1: Di
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For medium-sized contacts as in Fig
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Appendix C CONVERGENCE TRAPS FOR LO
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The case of Figure C.1b contains a
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in Figure C.2c would increase the a
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[12] D. P. Bertsekas. A distributed
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[37] Donald L. Fisher, Robert O. An
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[62] Ken Hinckley, Rand</st
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[87] Wendi Ann Latko. Development <
Page 359 and 360:
[111] Robert J. Miller, Stephen Bis
Page 361 and 362:
[136] John L. Sibert and</s
Page 363:
[161] Wayne Westerman and</
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Hand Tracking, Finger Identification, and Chordic Manipulation on

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