We present a method to enable multi-touch interactions on an

arbitrary flat surface using a pair of cameras mounted above

the surface. Current systems in this domain mostly make use

of special touch-sensitive hardware, require cameras to be

mounted behind the display, or are based on infrared sensors

used in various configurations. The very few that use ordinary

cameras mounted overhead for touch detection fail to

do so accurately due to the difficulty in computing the proximity

of fingertips to the surface with a precision that would

match the behaviour of a truly touch-sensitive surface. This

paper describes a novel computer vision algorithm that can

robustly identify finger tips and detect touch with a precision

of a few millimetres above the surface. The algorithm relies

on machine learning methods and a geometric finger model

to achieve the required precision, and can be ‘trained’ to

work in different physical settings. We provide a quantitative

evaluation of the method and demonstrate its use for gesture

based interactions with ordinary tablet displays, both in single

user and remote collaboration scenarios.

PDF file

In  Second IEEE International Workshop on Horizontal Interactive Human-Computer Systems (Tabletop 2007)

Publisher  IEEE
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