zhao, 2001 synthesis laban gesture
TRANSCRIPT
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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
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- XDXD
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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
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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
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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
Y
o
y
s sw
wz
x
-
s
y
z
w
a
b
vdz
Z
Y
w
ver>0 &&
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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~
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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
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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
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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
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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
e
0 50 1002
4
6
8
10
max wrist angle
swiv
el z
ero
cros
sing
s
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
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3DEstimation
FeatureExtraction
ExpressiveMotionEngine(EMOTE)
ImageAnalysis
ImageAnalysis
Camera 1
Camera 2
...
keystructure
Style
Noisefiltering
EMOTEparameters
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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
y y
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
s
2D Data (Direct Space)
0200
400
0200
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
200
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