Textured Surface Interaction: Velocity and position estimation with frequency domain signatures
Farid Rener
In
du o With the explosion of ubiquitous computing comes the trneed for cheap and simple input devices. Expensive multi-touch
on ti c
McGill University
Applications
a)
Prior
Harrison et. al, ‘Scratch Input’ [5]
Work
interfaces such as the iPhone, Reactable and Microsoft Surface have stretched the ways we communicate and interact with computers and other electronic objects. As more and more items in our daily lives are 'smartified' new ways of providing information to these items is required. Many of these simple devices only require position and velocity information to perform their tasks, for instance flicking through a digital photo album or jukebox. While velocity and position estimation can be used in many different contexts, the motivating application is in floor surfaces to determine footground velocity information. Presented here is a method of determining velocity and position using an inexpensive textured surface and piezo-electric microphone for use as a scalable input device.
b)
c) Some proposed applications of Textured Surface Interaction Device. a) Tablet, b) Interactive Floor Surface [3], c) Digital Photo Album [3].
Kim et. al, ‘A gestural input through finger writing on a textured pad’ [4]
Murray - Smith et. al, ‘Stane: Synthesized Surfaces for tactile input’ [2]
F
mputation Co ce r o
Force exerted by textured block on stylus is computed with Minsky’s Sandpaper model:
F = -k∇h(x,y)
Ideally, the piezo-sensor sees ‘F’.
Surface texture is designed to produce this spectrum when impulsed in one direction:
Te
re Design tu x
Position Codes
e T
Using texture pads with many sidebands, it is possible to encode position by interpreting different signatures as a ‘code’.
e Equation xtur
The sidebands are different for x & y components.
i ss Signal Proce
g n
With prior knowledge of the surface texture and the relative distance of the sidebands from the centre frequencies, peak detection can be used to extract the x & y components from the Short-Time-FourierAmplitude 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 computed from the known ‘centre frequency’ of the texture pad. For one trajectory across two codes, the following output is obtained: The velocity can be seen in blue and the code in red.
Frequency (Hz)
Implementation Realtime
A realtime implementation is being set-up in the Max/MSP environment for both simulation and use.
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.
Acknowledgments
[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, Stane: synthesized surfaces for tactile input, 2008. [3] Microsoft Research, “Being Human: Human-Computer Interaction in the Year 2020”, April 2008. [4] Kim, J.E. and Sunwoo, J. and Son, Y.K. and Lee, D.W. and Cho, I.Y., A gestural input through finger writing on a textured pad, CHI '07 extended abstracts on Human factors in computing systems, San Jose, CA, 2007 [5] Harrison, C. and Hudson, S.E., Scratch input: creating large, inexpensive, unpowered and mobile finger input surfaces, ACM, 2008
References