Pseudo Haptic in Augmented Reality Environment Based on Touchscreen

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Augmented Reality (AR) is a term that allows virtual object augmented into physical real world, in AR environment, human perception could help virtual object mixing with real environment to intensify its reality. Human's sensory sometimes make a cross effect on each other, by controlling visual effects and interactive feedback on touch-screen, we could take advantage of cross-sensory interaction to create a tactile illusion called pseudo-haptic.

Technology

Pseudo Haptic
in Augmented Reality Environment
Based on Touch Screen
Chien-Hsu, Chen / Ya-Hsin, Horng / Fong-Gong, Wu
National Cheng-kung University, Industrial Design department
chenhsu@mail.ncku.edu.tw

In Augment Reality (AR)
environment, human perception
could help virtual object mixing
with real environment to
intensify its reality.

By controlling visual effects
and interactive feedback on
touch-screen.
We could take advantage of
cross-sensory interaction to
create a tactile illusion called
pseudo-haptic.

Augmented Object
Real World
Mix World
Tablet with camera
Real Object
AUGMENT REALITY IN TOUCH-SCREEN ENVIRONMENT

Spatial
Presence
Tactile
Engagement
Sensory
Presence
Visual-to-
Tactile
Illusion
Presence
Cross-Modal Illusion
(Synesthesia)
RELATIONSHIP BETWEEN PRESENCE
AND CROSS-MODAL ILLUSIONS

Message
Visual
Auditory
Haptic
Stimuli
Image
Physical property
Sound noise
Variable
Visual effect
Sound effect
Control feedback
Sensation Perception
COGNITIVE MODULE OF PSEUDO-HAPTIC AR

Experiment
Control Group (Visual Only )
Experimental Group (Pseudo Haptic)

Figure 1. Three rounds in control
group. (A) elasticity (B) density (C)
friction.
CONTROL GROUP

Figure 2. Three rounds in passive visual
clue only. (A) elasticity (B) density (C)
friction.
EXPERIMENTAL GROUP

Result
liner regressions
accuracy
volume

LINER REGRESSION
1.187
1.028
1.187
1.133
1.15
1.274
1.084
1.132
1
1.05
1.1
1.15
1.2
1.25
1.3
Elasticity Density Friction All
Slpoevalueoftheregression
Control Group Experimental Group
0.970 0.698 0.933 0.859
0.974
0.761
0.938
0.874
0.6
0.65
0.7
0.75
0.8
0.85
0.9
0.95
1
Elasticity Density Friction All
Rsquare
Figure 3 (UP) Slope values
calculated through a linear
regression for each condition.
(Down) R square for each condition.
The fourth condition is the group
average.

PHYSICAL PROPERTY
0
0.2
0.4
0.6
0.8
1
1.2
1 2 3 4 5 1 2 3 4 5 1 2 3 4 5
Deviation
Big Middle Small
elastic Density Friction
0
0.2
0.4
0.6
0.8
1
1.2
1 2 3 4 5 1 2 3 4 5 1 2 3 4 5
Deviation
Big Middle Small
Figure 4 (Up) Mean deviation
of allocated score in control
group. (Down) Mean
deviation of allocated score
in experimental group.

VOLUME
0.925 1.128 0.881
0.684
0.896
0.830
0.702
1.191
0.967
0.4
0.5
0.6
0.7
0.8
0.9
1
1.1
1.2
1.3
1.4
Elasticity Denisty Friction
Deviation
Big Middle Small
0.844 1.029 0.758
0.681
1.078
0.793
0.543
1.335
0.839
0.4
0.5
0.6
0.7
0.8
0.9
1
1.1
1.2
1.3
1.4
Elasticity Denisty Friction
Deviation
Figure 5 Mean deviation which
sorting by the sample volume in
(Up) Control group. (Down)
Experimental group.

EXPERIMENT
 Value of R2 and the slope of the regression in
experimental group represent better than control
group.
 Participant’s allocated score is in direct ratio to the
actual parameter, but the accuracy of reported value is
not quite high.
 Mean of deviation of control group is 0.914, the
experiment group has the lower mean as 0.878. (T-test,
α=95%, p=0.605)

DISCUSSION
FUTURE WORK
Correlation coefficients of accuracy and time in a
single task.
Participant’s workload.
The subjective scale of preferences.
POSSIBILITY
Increasing physical fidelity on AR platform without
extra space.
Helpful on video game or virtual interface, enhance
the effect of motion sensing and the depths of
presence

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1. Pseudo Haptic in Augmented Reality Environment Based on Touch Screen Chien-Hsu, Chen / Ya-Hsin, Horng / Fong-Gong, Wu National Cheng-kung University, Industrial Design department chenhsu@mail.ncku.edu.tw

2. In Augment Reality (AR) environment, human perception could help virtual object mixing with real environment to intensify its reality.

3. By controlling visual effects and interactive feedback on touch-screen. We could take advantage of cross-sensory interaction to create a tactile illusion called pseudo-haptic.

4. Augmented Object Real World Mix World Tablet with camera Real Object AUGMENT REALITY IN TOUCH-SCREEN ENVIRONMENT

5. Spatial Presence Tactile Engagement Sensory Presence Visual-to- Tactile Illusion Presence Cross-Modal Illusion (Synesthesia) RELATIONSHIP BETWEEN PRESENCE AND CROSS-MODAL ILLUSIONS

6. PSEUDO-HAPTIC AR SYSTEM ON TOUCH SCREEN

7. Message Visual Auditory Haptic Stimuli Image Physical property Sound noise Variable Visual effect Sound effect Control feedback Sensation Perception COGNITIVE MODULE OF PSEUDO-HAPTIC AR

8. Experiment Control Group (Visual Only ) Experimental Group (Pseudo Haptic)

9. Figure 1. Three rounds in control group. (A) elasticity (B) density (C) friction. CONTROL GROUP

10. Figure 2. Three rounds in passive visual clue only. (A) elasticity (B) density (C) friction. EXPERIMENTAL GROUP

11. Result liner regressions accuracy volume

12. LINER REGRESSION 1.187 1.028 1.187 1.133 1.15 1.274 1.084 1.132 1 1.05 1.1 1.15 1.2 1.25 1.3 Elasticity Density Friction All Slpoevalueoftheregression Control Group Experimental Group 0.970 0.698 0.933 0.859 0.974 0.761 0.938 0.874 0.6 0.65 0.7 0.75 0.8 0.85 0.9 0.95 1 Elasticity Density Friction All Rsquare Figure 3 (UP) Slope values calculated through a linear regression for each condition. (Down) R square for each condition. The fourth condition is the group average.

13. PHYSICAL PROPERTY 0 0.2 0.4 0.6 0.8 1 1.2 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 Deviation Big Middle Small elastic Density Friction 0 0.2 0.4 0.6 0.8 1 1.2 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 Deviation Big Middle Small Figure 4 (Up) Mean deviation of allocated score in control group. (Down) Mean deviation of allocated score in experimental group.

14. VOLUME 0.925 1.128 0.881 0.684 0.896 0.830 0.702 1.191 0.967 0.4 0.5 0.6 0.7 0.8 0.9 1 1.1 1.2 1.3 1.4 Elasticity Denisty Friction Deviation Big Middle Small 0.844 1.029 0.758 0.681 1.078 0.793 0.543 1.335 0.839 0.4 0.5 0.6 0.7 0.8 0.9 1 1.1 1.2 1.3 1.4 Elasticity Denisty Friction Deviation Figure 5 Mean deviation which sorting by the sample volume in (Up) Control group. (Down) Experimental group.

15. Conclusion Experiment Discussion

16. EXPERIMENT  Value of R2 and the slope of the regression in experimental group represent better than control group.  Participant’s allocated score is in direct ratio to the actual parameter, but the accuracy of reported value is not quite high.  Mean of deviation of control group is 0.914, the experiment group has the lower mean as 0.878. (T-test, α=95%, p=0.605)

17. DISCUSSION FUTURE WORK Correlation coefficients of accuracy and time in a single task. Participant’s workload. The subjective scale of preferences. POSSIBILITY Increasing physical fidelity on AR platform without extra space. Helpful on video game or virtual interface, enhance the effect of motion sensing and the depths of presence

18. END THANKS FOR YOUR ATTENTION

Editor's Notes

In the occasion of cross-modal effect, the perception of a sensation is altered due to other stimuli that are received through the other senses in the meantime. However, individual would make up a deficiency sense by another sensory in some cases, come up an integrated perception by incomplete factor
When an individual controls a virtual object on the touch screen, the target object will not react in real-time, but will, instead present an adjusted deviation between normal situations. The unexpected visual feedback causes a sense of unbalance between our perception and our expectation; this leads to a corrected instruction from brain which makes body follow the adjusted speed unconsciously. At the same time, the tactile information on the skin also changes because of the revised movement and perception and sensation synchronize with each other gradually. When both of them reach equilibrium, the brain accepts a concept of their realism and an illusion of virtual physics property is constituted successfully
Message Level: it represents the raw data (e.g., visual, auditory) which received by human sensory. Stimuli Level: stimuli are energy patterns which are registered by the senses. After distilling the raw message, the basic elements of sensation are given (e.g., color or physical property of an object). Variable Level: The formation of a specific perception (e.g., appearance or the features of an object).
This study probe into the interaction between user and touch-screen AR device, focused on the variation after user get the target. The experiment inspired by Nusseck’s path prediction test (Nusseck, et al., 2007), carrying out two sections; each experimental environment is constrained to a simple object interaction. The control group only contains passive visual clue, the experimental group includes interactive feedback.
The results of experiments would be separated into three values to discuss:
Compare to the slope value of control group, the same parameter in experiment group are closer to 1. All specific values in both groups are bigger than 1, that means the actual value is generally bigger than the estimated one, and the trend of prediction in experiment group is more similar to the exact value. As for the R2 value of liner regression, the correlation coefficients for these conditions are quite high in both elasticity and friction rounds. The R square in experimental group condition is higher than the other of control group which reveals that by adding passive visual clue, the sample in experiment group shows a better correlation with the correct number.
The line chart of deviation of all 15 samples sketch a rough trend of 3 wave; the middle level such like 2,3 and 4 have higher deviation than level 1 and 5; the higher deviation means those situations are harder to be predicted closely with correct ones. the performance of participants improves in elasticity and friction round instead the deviation of density round raised. It shows the addition of dynamic clue and interactive feedback can possibly revise the performance of participants in appraising bounce and slide motion, making their prediction closer to the exact value in experiment environment.
Over all, sample unite of middle volume has the highest accuracy of prediction; on the other hand, samples of big and small volume are easier been valued with bias . In experimental group, participants recognizes elasticity and friction more efficiency in all condition, however the addition of interactive feedback causes clear deviations in density round except big volume sample unite.
The results of experiments would be separated into three values to discuss:

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