Hand Tracking, Finger Identification, and Chordic Manipulation on

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h<strong>and</strong> con guration. This integration technique depends upon reliable detection of synchronized nger touches, extraction of independent h<strong>and</strong> translation, scaling, <strong>and</strong> rotational velocities, <strong>and</strong> the aforementioned nger <strong>and</strong> h<strong>and</strong> identi cations. The MTS optimizes ergonomics by eliminating redundant pointing <strong>and</strong> homing motions, minimizing device activation force without removing support for resting h<strong>and</strong>s, <strong>and</strong> distributing tasks evenly over muscles in both h<strong>and</strong>s. Based upon my daily use of a prototype to prepare this document, I have found that the MTS system as a whole is nearly as reliable, much more e cient, <strong>and</strong> much less fatiguing than the typical mouse-keyboard combination. xxx
Chapter 1 INTRODUCTION 1.1 The State of <strong>H<strong>and</strong></strong>-Computer Interaction in 1998 In the rst paper to formally demonstrate the advantages of two-h<strong>and</strong>ed graphical manipulation, e.g. scrolling with one h<strong>and</strong> while pointing with the other, Buxton <strong>and</strong> Myers [23] lament: To date, very few computer systems easily lend themselves to experimentation with the types of interaction described in this paper. Twelve years later, further research [62, 86, 171] has veri ed the e ciency <strong>and</strong> in- tuitiveness of simultaneous two-h<strong>and</strong>ed manipulation <strong>and</strong> high degree-of-freedom (DOF) controls. Manually dem<strong>and</strong>ing tasks such as web browsing <strong>and</strong> computer- aided- design (CAD) have also become ubiquitous, but the requisite input devices have yet to appear on the personal computer market. As Leganchuk et al. [90] point out, One reason for this may be the di culty in equipping systems with inexpensive <strong>and</strong> available input devices capable of capturing bimanual input. Enthusiastic investigation of gesture recognition via alternative input devices has also lulled since pen computing, data gloves, <strong>and</strong> ergonomic keyboards failed to blossom in the early 1990s. Hope for improvement in human-computer interaction has shifted to speech recognition, but speech is clearly inappropriate for precise manipulation of graphics. Computer manufacturers seem to have concluded that 1
Page 1 and 2: HAND TRACKING, FINGER IDENTIFICATIO
Page 3 and 4: Signed: Signed: Signed: Signed: Sig
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: ABSTRACT This research introduces m
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
Page 53 and 54: the nger synchronization detector w
Page 55 and 56: very important preventive measures
Page 57 and 58: 1.6.2.5 Minimize user anticipation
Page 59 and 60: extracted from hand</strong
Page 61 and 62: language as they appear in communic
Page 63 and 64: 2.1.5 Sensing Finger</stron
Page 65 and 66: a) b) c) d) Figure 2.2: Projection
Page 67 and 68: a) b) c) d) Figure 2.3: Ambiguities
Page 69 and 70: few millimeters of the electrodes.
Page 71 and 72: 41 Vertical Position on Surface (Y
Page 73 and 74: 2.1.9 No Motion Blur on MTS Another
Page 75 and 76: position is indicated by the amount
Page 77 and 78: The o set-corrected image E is then
Page 79 and 80: 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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113 Vertical Position on Surface (Y
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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
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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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