Scale-space based feature point detection for digital ink

Authors:
Tevfik Metin Sezgin;Randall Davis
Affiliations:
MIT Computer Science and Artificial Intelligence Laboratory, Cambridge MA;MIT Computer Science and Artificial Intelligence Laboratory, Cambridge MA
Venue:
ACM SIGGRAPH 2007 courses
Year:
2007

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Abstract

Feature point detection is generally the first step in model-based approaches to sketch recognition. Feature point detection in free-hand strokes is a hard problem because the input has noise from digitization, from natural hand tremor, and from lack of perfect motor control during drawing. Existing feature point detection methods for free-hand strokes require hand-tuned thresholds for filtering out the false positives. In this paper, we present a threshold-free feature point detection method using ideas from the scale-space theory.