  We describe a sketch interpretation system that detects and classifies clock
numerals created by subjects taking the Clock Drawing Test, a clinical tool
widely used to screen for cognitive impairments (e.g., dementia). We describe
how it balances appearance and context, and document its performance on some
2,000 drawings (about 24K clock numerals) produced by a wide spectrum of
patients. We calibrate the utility of different forms of context, describing
experiments with Conditional Random Fields trained and tested using a variety
of features. We identify context that contributes to interpreting otherwise
ambiguous or incomprehensible strokes. We describe ST-slices, a novel
representation that enables "unpeeling" the layers of ink that result when
people overwrite, which often produces ink impossible to analyze if only the
final drawing is examined. We characterize when ST-slices work, calibrate their
impact on performance, and consider their breadth of applicability.
