Textured Surface Interaction: Velocity and position
estimation with frequency domain signatures
Farid Rener
McGill University
c tion Applications Prior
du
o With the explosion of ubiquitous computing comes the
trneed for cheap and simple input devices. Expensive multi-touch
Work
In
Harrison et. al, ‘Scratch Input’ [5]
interfaces such as the iPhone, Reactable and Microsoft Surface have
a)
stretched the ways we communicate and interact with computers and
other electronic objects. As more and more items in our daily lives are 'smar-
tified' new ways of providing information to these items is required. Many of Kim et. al, ‘A gestural input through
finger writing on a textured pad’ [4]
c)
these simple devices only require position and velocity information to perform Some proposed applications of
their tasks, for instance flicking through a digital photo album or jukebox. Textured Surface Interaction
Device. a) Tablet, b) Interactive
While velocity and position estimation can be used in many different con- Floor Surface [3], c) Digital
b) Photo Album [3].
texts, the motivating application is in floor surfaces to determine foot- Murray - Smith et. al, ‘Stane: Synthesized
Surfaces for tactile input’ [2]
ground velocity information.
Presented here is a method of determining velocity and
Computation
position using an inexpensive textured surface and
rce
piezo-electric microphone for use as a
scalable input device. o
F
Force exerted by textured block on stylus is com-
puted with Minsky’s Sandpaper model:
F = -k∇h(x,y)
Ideally, the piezo-sensor sees ‘F’.
x tu re Design
Te
Surface texture is designed to
produce this spectrum when impulsed
in one direction:
xture Equation The sidebands are different for x & y
Te components.
Position Codes
Using texture pads with many sidebands, it
n g
i
is possible to encode position by interpret-
ss
ing different signatures as a ‘code’.
Signal Proce
With prior knowledge of the surface texture and the relative dis-
tance of the sidebands from the centre frequencies, peak detection can be used to extract
the x & y components from the Short-Time-Fourier-
Amplitude Spectrum of resulting signal, showing x and y
Transform of the signal obtained by the sensor. components (coloured circles)
Velocity Estimation
Once the x & y components and the position code is known, the velocity can be com-
puted from the known ‘centre frequency’ of the texture pad. For one trajectory across
two codes, the following output is obtained:
Frequency (Hz)
The velocity can be seen in blue and the
code in red.
References
[1] M. Minsky. “Computational Haptics: The Sandpaper System
for Synthesizing Texture for a Force-Feedback Display.” Ph.D. thesis,
Ph.D. Dissertation, Program in Media Arts and Sciences, MIT, 1995.
[2] Murray-Smith, R. and Williamson, J. and Hughes, S. and Quaade, T,
Implementation
Stane: synthesized surfaces for tactile input, 2008.
[3] Microsoft Research, “Being Human: Human-Computer Interaction in
the Year 2020”, April 2008.
Realtime
[4] Kim, J.E. and Sunwoo, J. and Son, Y.K. and Lee, D.W. and Cho, I.Y., A
A realtime implementation is being gestural input through finger writing on a textured pad, CHI '07 extended
set-up in the Max/MSP environment for abstracts on Human factors in computing systems, San Jose, CA, 2007
both simulation and use. [5] Harrison, C. and Hudson, S.E., Scratch input: creating large, inexpen-
sive, unpowered and mobile finger input surfaces, ACM, 2008
Acknowledgments
This work would have been impossible without the patient help of Yon Vissel.
Thanks to everyone at the Shared Reality Environment lab, and especially to
Professor Jeremy Cooperstock.