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Design Method of 3D-Printable
Ergonomically Personalized Stabilizer
Ryota Kawamura1, Kazuki Takazawa1, Kenta Yamamoto1, Yoichi Ochiai1,2
1University of Tsukuba, 2Pixie Dust Technologies, Inc
2
BACKGROUND
3
Why We Need Stabilizer
Blurry Video
No Stabilizer, No Unblurry Video
Shooting with
Moving Target
4
Image Stabilization
How to realize Stabilization
Optical Method Electronic Method
[Oshima, Mitsuaki, et al. 1989]
[Liu, Shuaicheng, et al. 2014]
[Liu, Shuaicheng, et al. 2013]
5
Gimbal Stabilizer
• Need Technical Skills
• Heavy
• Expensive
Hand-held Attached to the user
How to realize Stabilization
6
Personalized Stabilizer
Hand-held Attached to the user
Mass Produced
Order Maid
Personalized
Ours
History of Manufacturing
7
Study01: Exo-Balancer
8
Assembly Process
(i) 3D Printing
(ii) Assembling Parts
(iii) Attaching Stabilizer
How to carry out our method
A
B
C
F
F
n
l
L
x
θa
θb
camera
mc
mf
9
Force Relationship
• Ask the user for the position of
natural holding
• Under the condition of F=F’
• Derive x and l
Force Relationship Equations
How to carry out our method
10
Experimental Protocol
How Effective Our Method is
Participants
8 people; age: 18~25
Experimental Procedure
Continue to shoot for 30s
the sphere moving within
the projected area
11
Experimental Protocol
Experimental method list
A) Proposed Method
B) Proposed Method +50mm (x)
C) Proposed Method -50mm (x)
H) Without Proposed Method
B and C are given error values to the proposed method.

H is not using the proposed method.
A
B
C
F
F
n
l
L
x
θa
θb
camera
mc
mf
How Effective Our Method is
12
Quantitative Evaluation
Acceleration sensor fixed to the camera
Start End
Trajectory of a sphere projected on a wall
iPhone6 as an Acceleration Sensor
Comparing camera shake by acceleration value
How Effective Our Method is
13
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0 30.00 30.00 30.0Time [sec] Time [sec] Time [sec]
Acceleration[G]Acceleration[G]Acceleration[G]
A-B
A-B
A-B
A-C A-H
A-H
A-H
A-C
A-C
XXX
Y
Z Z Z
Y Y
Quantitative Evaluation
A-B: 

No Noticeable Difference
A-C: 

C reduced the camera shake
How Effective Our Method is
Experimental method list
A) Proposed Method
B) Proposed Method +50mm (x)
C) Proposed Method -50mm (x)
H) Without Proposed Method
14
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!"$
!"%
&
&"&
&"'
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!
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0 30.030.0me [sec] Time [sec]
A-H
A-H
A-H
XX
Z Z
Y Y
Quantitative Evaluation
A-H: 

Camera shake is smaller in H
How Effective Our Method is
Experimental method list
A) Proposed Method
B) Proposed Method +50mm (x)
C) Proposed Method -50mm (x)
H) Without Proposed Method
15
Qualitative Evaluation
Q1: This method is easy to take photos.
Q2: You feel this method is stable.
Q3: You feel tired when using this shooting method.
Q4: This method is designed to personalize your body.
Q5: How enjoyable it this method?
Q6: How stressed when you are took in this way?
Question List (Likert Scale)
How Effective Our Method is
16
Q1
Q2
Q3
1 2 3 4 5
Q4
Q5
Q6
This method is easy
to take photos.
You feel this method
is stable.
You feel tired when
using this shooting method.
This method is designed to
personalize your body.
How enjoyable it this method?.
How stressed when
you are took in this way?
!
"
#
$
!
"
#
$
!
"
#
$
!
"
#
$
!
"
#
$
!
"
#
$
SDM
Strongly disagree Neutral Strongly agree
H
A
B
C
H
A
B
C
H
A
B
C
H
A
B
C
H
A
B
C
H
A
B
C
Wilcoxon signed rank test was performed.
Statistically significant difference was only
found between C and H in Q6.
Self-attribution tends to be higher if fixed
as in the proposed method.
Qualitative Evaluation
How Effective Our Method is
17
Study01: Summary
No Stabilizer, No Unblurry Video
Quantitative
It is less likely to blur on hand than this method.
Qualitative
Self-attribution is enhanced by the fixation
mechanism.
Positive response for personalization with this
method.
18
Study01: Problem
No Stabilizer, No Unblurry Video
1.Low durability because of the property of
ready-made goods
2.Low adaptability for physically characterized
people
3.Low stabilizing ability
19
Study01: Problem
No Stabilizer, No Unblurry Video
1.Low durability because of the property of
ready-made goods
2.Low adaptability for physically characterized
people
3.Low stabilizing ability
→All 3D Printed
→Modify Optimization Method
→Update Stabilization Mechanism
20
Study02: Topological Approach
21
Structure Optimization
Next Optimization Approach
Our next

approach
Structure Optimization

(Topology Optimization)
Demension Optimization
(Changing Parameters)
Shape Optimization

(Changing Border)
Our first

approach
22
Re-Design Process
camera
Define Parameters
along Force Equations
Topology Optimization
Pitch Directional Stabilization
First Approach
Advanced Approach
3D Printing
Assemble
Ready-Made Parts
Renew Our Design Process
All 3D Printed

Parts
3D Printed Objects

with Ready-Made Parts
23
Topological Optimization
How to optimize Topology
Base Form
4 Supporting Points
Loaded Surface
Result and Attachment
24
Topological Optimization
Perspective
View
Right
View
Iteration
n = 10 n = 70n = 50n = 30
Results of Topology Optimization
Shape Results after Iterations
25
Stabilization Accessories
Pitch Directional
Stabilizer for
Compact Camera
Updating Stabilization Mechanism
26
Discussion
For Next Research
3D Model after Topology Optimization with laplacian smoothing
Thank You
Ryota Kawamura1, Kazuki Takazawa1, Kenta Yamamoto1, Yoichi Ochiai1,2
1University of Tsukuba, 2Pixie Dust Technologies, Inc
Design Method of 3D-Printable
Ergonomically Personalized Stabilizer

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Design Method of 3D Printable Ergonomically Personalized Stabilizer - HCII 2019 presentation