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  • Department of Computer & Information Science

    Technical Reports (CIS)

    University of Pennsylvania Year 2001

    Synthesis and Acquisition of Laban

    Movement Analysis Qualitative

    Parameters for Communicative Gestures

    Liwei Zhao

    Norman I. Badler

    University of Pennsylvania

    University of Pennsylvania, [email protected]

    This paper is posted at ScholarlyCommons.

    http://repository.upenn.edu/cis reports/116

  • XD
  • XDXDXDXDXDXD
  • XDXDXDXD
  • XDXDXDXDXD
  • XDXDXDXD
  • XDXDXDXD
  • XDXD
  • Discourse modelsituation knowledge

    encyclopaedia

    Longtermmemory

    Workingmemory

    Conceptualizer

    Others

    Propositional Spatial/Dynamic

    Formulator

    Grammaticalencoder

    Phonologicalencoder

    Articulator

    Auditorymonitor

    Lemma

    Wordforms

    Spatial/dynamicfeature selector

    Motor planner

    Motor system

    Kinesic monitor

    Lexicon

    overtspeech

    preverbal message

    phoneticplans

    spatial/dynamic feature

    motor program

    lexical movement

  • XD
  • semantic filteringtemporal filteringunification

    statistical weightingneural computingpolicy and planning

    user input

    speech recognition gesture recognition

    gestural languageinterpretation

    spoken languageinterpretation

    speech generation gesture generation

    user

    multimodalinterface

    psychologicalor cognitivemodels

    embodiedconversational agent models

  • XDXDXDXDXDXDXDXD
  • wrist

    elbow

    waist

    shoulder

    clavicle

    hip

    neck

    knee

    spine

  • S

    ShoulderJoint

    WristJoint

    WElbowJoint E

    R

    c

    u

    a

    ve

    n

    ew

    w

  • s

    y

    z

    w

    w

    a

    b

    A

    vdy vdz

    Z

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    o

    y

    s sw

    wz

    x

  • s

    y

    z

    w

    a

    b

    vdz

    Z

    Y

    w

    ver>0 &&

  • C

    ShoulderJoint

    S

    O

    WristJoint

    WCenterof Mass

    W"W

    w c

    vu

    XZ

    Y

    origin

    XZ

    Y

    t

    s

  • XD
  • c

    u

    n

    Pe( )

    Pe

    P

    P~

  • 1 2 3 4 5 6 7 8 9 10 11 120

    0.1

    0.2

    0.3

    0.4

    0.5

    0.6

    0.7

    0.8

    0.9

    motion samples

    Spon

    tane

    ity

    BoundFlow FreeFlow NeutralFlow

  • 0 100 200 3000

    0.1

    0.2

    0.3

    0.4

    0.5DirectStrong

    curv

    atur

    e

    0 100 200 3000

    200

    400

    600

    800DirectStrong

    curv

    atur

    e0 200 400 600

    0

    0.1

    0.2

    0.3

    0.4

    0.5Neutral

    curv

    atur

    e

    0 200 400 6000

    100

    200

    300

    400Neutral

    curv

    atur

    e

    0 200 400 600 8000

    0.1

    0.2

    0.3

    0.4

    0.5IndirectLight

    frame number

    curv

    atur

    e

    0 200 400 600 8000

    50

    100

    150IndirectLight

    frame number

    curv

    atur

    e

  • S

    ShoulderJoint

    WristJoint

    WElbowJoint E

    R

    c

    u

    a

    ve

    n

    ew

    w

  • 0 500 100020

    40

    60

    80

    100Example 1

    swiv

    el a

    ngle

    s

    Indirect

    DirectNeutral

    0 500 10000

    50

    100Example 2

    Indirect

    DirectNeutral

    0 100 200 30020

    40

    60

    80Example 3

    Indirect

    DirectNeutral

    0 100 200 3000

    20

    40

    60Example 4

    swiv

    el a

    ngle

    Indirect

    Direct

    Neutral

    0 100 200 30020

    40

    60

    80

    100Example 5

    Indirect

    Direct

    Neutral

    0 100 200 3000

    20

    40

    60

    80Example 6

    Indirect

    Direct

    Neutral

    0 100 200 3000

    20

    40

    60Example 7

    swiv

    el a

    ngle

    IndirectDirectNeutral

    0 200 4000

    20

    40

    60

    80Example 8

    IndirectDirect Neutral

    0 100 200 3000

    20

    40

    60Example 9

    Indirect

    DirectNeutral

    0 100 200 3000

    50

    100Example 10

    frame number

    swiv

    el a

    ngle

    Indirect

    Direct Neutral

    0 100 200 30010

    20

    30

    40

    50Example 11

    frame number

    IndirectDirect

    Neutral

    0 100 200 3000

    50

    100Example 12

    frame number

    Indirect

    Direct

    Neutral

  • 0 200 400 600 80020

    40

    60

    80

    100Example 1

    swiv

    el a

    ngle

    s

    Indirect

    Direct

    Neutral

    0 200 400 600 80050

    0

    50

    100Indirect

    indirect normalizedlow freq high freq

    0 200 400 60020

    0

    20

    40

    60

    80

    100Neutral

    frame number

    swiv

    el a

    ngle

    s

    neutral normalizedlow freq high freq

    0 50 100 15030

    20

    10

    0

    10

    20

    Indirect_hfreq

    neutral_hfreq

    frame number

    Indirect vs Neutral

  • 0 200 400 6000

    20

    40

    60

    80Example 1

    wris

    t ang

    le IndirectDirectNeutral

    0 200 400 600

    20

    40

    60

    80

    Example 2

    IndirectDirect

    Neutral

    0 100 200 3000

    20

    40

    60

    80Example 3

    Indirect

    Direct Neutral

    0 100 200 3000

    20

    40

    60

    80Example 4

    wris

    t ang

    le

    Indirect

    DirectNeutral

    0 100 200 3000

    50

    100Example 5

    Indirect

    DirectNeutral

    0 100 200 3000

    50

    100Example 6

    Indirect

    DirectNeutral

    0 100 200 3000

    50

    100Example 7

    wris

    t ang

    le

    Indirect

    Direct

    Neutral

    0 200 4000

    50

    100Example 8

    Indirect

    Direct

    0 100 200 3000

    20

    40

    60

    80Example 9

    Indirect

    Direct

    Neutral

    0 100 200 3000

    20

    40

    60

    80Example 10

    frame number

    wris

    t ang

    le

    Indirect

    Direct Neutral

    0 100 200 3000

    50

    100Example 11

    frame number

    IndirectDirect

    Neutral

    0 100 200 3000

    20

    40

    60

    80

    Example 12

    frame number

    IndirectDirect

    Neutral

  • 1 2 3 4 5 6 7 8 9 1011120

    2

    4

    6

    8

    10

    12

    motion samples

    ster

    num

    hei

    ght

    SuddenTime StrongWeight

    1 2 3 4 5 6 7 8 9 1011120

    1

    2

    3

    4

    5

    6

    7

    8

    9

    10

    motion samples

    ster

    num

    hei

    ght

    SustainedTimeLightWeight

  • W1,1W2,1WI,1

    W1,2W2,2WI,2

    W1,MW2,MWI,M

    InputLayer

    bias1

    XI

    X2

    X1

    hiddenLayer

    OutputLayerSigmoid

    functionSigmoid function

    bias1

    bias1

    bias1

    bias1

    h2

    h1

    hn

  • 0 50 1000

    50

    100

    150

    200

    velocity

    acce

    lera

    tion

    direct neutral indirect

    0 100 2000

    100

    200

    300

    400

    500

    600

    swivel velocity

    wris

    t vel

    ocity

    0 5 100

    2

    4

    6

    8

    10

    swivel zerocrossings

    wris

    t zer

    ocr

    ossi

    ngs

    0 0.5 1 1.50

    0.1

    0.2

    0.3

    0.4

    curvature

    tors

    ion

    direct neutral indirect

    0 50 100 1500

    20

    40

    60

    80

    100

    120

    swivel angle sum

    wris

    t pen

    dulu

    m s

    um (s

    cale

    d)

    20 40 60 800

    20

    40

    60

    80

    100

    swivel angle

    max

    wris

    t ang

    le

    0 50 1000

    20

    40

    60

    80

    100

    swivel minmax diff

    wris

    t max

    ang

    le

    0 50 1000

    0.5

    1

    1.5

    velocity

    curv

    atur

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    0 50 1002

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    6

    8

    10

    max wrist angle

    swiv

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    direct neutral indirect

  • 0 500 1000 15000

    0.05

    0.1

    0.15

    0.2

    0.25

    0.3

    0.35

    Number of weight updates (in hundreds)

    Erro

    r

    Error versus weight updates (BPNN 0)

    Training error Validation error

    0 500 1000 15000

    0.05

    0.1

    0.15

    0.2

    0.25

    0.3

    0.35

    Number of weight updates (in hundreds)

    Erro

    r

    Error versus weight updates (BPNN 1)

    Training error Validation error

    0 100 200 300 4000

    0.05

    0.1

    0.15

    0.2

    0.25

    0.3

    0.35

    Number of weight updates (in hundreds)

    Erro

    r

    Error versus weight updates (BPNN 2)

    Training error Validation error

    0 500 1000 15000

    0.05

    0.1

    0.15

    0.2

    0.25

    0.3

    0.35

    Number of weight updates (in hundreds)

    Erro

    r

    Error versus weight updates (BPNN 3)

    Training error Validation error

  • 3DEstimation

    FeatureExtraction

    ExpressiveMotionEngine(EMOTE)

    ImageAnalysis

    ImageAnalysis

    Camera 1

    Camera 2

    ...

    keystructure

    Style

    Noisefiltering

    EMOTEparameters

  • 1O 2O

    1P

    1P

    2P2P

    Q

    (x,y)1 1

    (x ,y )1 1

    (x ,y )2 2(x,y)2 2

    image plane

    xx

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    O

    1T 2T

    f2f1

    z z

    1(X ,Y ,Z )1 1 1(X ,Y ,Z )2 2 22Q(X,Y,Z)1 1 11Q

    (X,Y,Z)2 2 22Q

  • 100 150 200 250 300 350 4000

    100

    200

    300

    400

    x coordinates

    y co

    ordi

    nate

    s

    2D Data (Neutral Space)

    0200

    400

    0200

    400600

    200

    0

    200

    x coordinates

    3D Data (Neutral Space)

    y coordinates

    200 250 300 350 400100

    150

    200

    250

    300

    350

    x coordinates

    y co

    ordi

    nate

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    2D Data (Direct Space)

    0200

    400

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    400600

    200

    0

    200

    x coordinates

    3D Data (Direct Space)

    y coordinates

    150 200 250 300 350 400100

    150

    200

    250

    300

    350

    x coordinates

    y co

    ordi

    nate

    s

    2D Data (Indirect Space)

    0200

    4000

    200400

    600

    200

    0

    200

    x coordinates

    3D Data (Indirect Space)

    y coordinates

  • 100 150 200 250 300 350 40050

    100

    150

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    250

    300

    350

    400

    x coordinates

    y co

    ordi

    nate

    s

    2D Data (Neutral Weight)

    2000

    200400

    0200

    400600

    200

    100

    0

    100

    200

    x coordinates

    3D Data (Neutral Weight)

    y coordinates

    200 250 300 350 400

    100

    150

    200

    250

    300

    350

    x coordinates

    y co

    ordi

    nate

    s

    2D Data (Strong Weight)

    0200

    400

    0200

    400600

    300200100

    0100200

    x coordinates

    3D Data (Strong Weight)

    y coordinates