Sketched symbol recognition with few examples using particle filtering

Abstract

Sketching is a natural form of user interface that is employed in a variety of areas, such as engineering drawings or classroom teaching. Recognition of hand drawn sketches is a challenging problem due to the variability in hand drawing, variability in the drawing order of strokes, and the similarity of sketch classes. In this work, we present a system that can classify hand drawn symbols using few examples. The quality of the alignment between two symbols is measured and used to asses the similarity between these symbols. We present recognition experiments using the COAD and the NicIcon databases with promising results.