Envisioning Sketch Recognition: A Local Feature Based Approach to Recognizing Informal Sketches

Michael Oltmans

Summary

Oltmans presents a vision-based approach to sketch recognition. Oltmans' approach uses visual parts of a shape to classify. Using a polar grid structure resembling a bullseye, feature vectors are calculated for parts of a stroke based on the ink density for each cell in the bullseye. A codebook is created which contains a standard vocabulary of parts. Input parts are compared with codebook parts, and a match vector is calcuated based on the differences. The match vectors for a training set are used to train a classifier, which can then classify an input stroke based on the match vectors of its respective parts.

Discussion

This is an intersting vision-based sketch recogntion algorithm. It is simple in design, and has potential in both on-line and off-line recogntion of sketches. One of the biggest advantages I see with vision-based techniques is that over-tracing is not an issue. However, I can see an advantage in being able to recognize when a sketch is over-traced. It emphasizes a statement of importance from the user. Perhaps this is useful from contextual standpoint, and can help in recognition sketch when the over-traced part is only a part of the whole sketch.