Digital painters commonly use a tablet and stylus to drive software
like Adobe Photoshop. A high quality stylus with 6 degrees of
freedom (DOFs: 2D position, pressure, 2D tilt, and 1D rotation)
coupled to a virtual brush simulation engine allows skilled users
to produce expressive strokes in their own style. However, such
devices are difficult for novices to control, and many people draw
with less expensive (lower DOF) input devices. This paper presents
a data-driven approach for synthesizing the 6D hand gesture data
for users of low-quality input devices. Offline, we collect a library
of strokes with 6D data created by trained artists. Online, given a
query stroke as a series of 2D positions, we synthesize the 4D hand
pose data at each sample based on samples from the library that
locally match the query. This framework optionally can also modify
the stroke trajectory to match characteristic shapes in the style of
the library. Our algorithm outputs a 6D trajectory that can be fed
into any virtual brush stroke engine to make expressive strokes for
novices or users of limited hardware.