Hand Tracking, Finger Identification, and Chordic Manipulation on

1.4 Summary of Contributions
The work described in this dissertation breaks ground in the following areas:
segmentation of surface contacts in proximity images.
identi cation of thumb, ngertip, <strong>and</strong> palm contacts tracked across successive
images.
translation-invariant sorting of contact points with respect to the inter-attractor
angles of an attractor point template.
partitioning of contacts into left <strong>and</strong> right h<strong>and</strong>clusters.
extraction of independent, 4-DOF velocity parameters from multiple nger
paths.
integration of typing <strong>and</strong> pointing on the same surface via the distinction
between simultaneous <strong>and</strong> asynchronous nger touchdown.
While this is not the rst implementation of a multi-touch device [15, 17, 88, 89, 107],
it is the rst to fully develop the unique integration potential of such a system. I
have encountered <strong>and</strong> overcome many problems unique to proximity sensing along
the way.
Though proximity image segmentation is simpli ed by the fact that proxim-
ity images lack thebackground clutter <strong>and</strong> lighting variations which plague optical
images, the topology of proximity images also presents special challenges which
have not been addressed in previous image processing research. The most di cult
of these is the invisibility of h<strong>and</strong> parts which oat above the surface. Also, the
low resolution of the proximity sensing array compared to video cameras obscures
boundaries between adjacent contacts. The con icting segmentation needs of n-
gertips, thumbs, <strong>and</strong> palms are e ectively resolved via feedback of bootstrapped
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