Yu: A Domain-Independent System for Sketch Recognition

Comments

Summary

In this paper the author talks about a domain independent system for sketch recognition. In this he talks about stroke approximation through direction graphs, curvature graphs and feature area of the strokes.

Here uses a different approach for vertex detection by first trying to classify a stroke into a primitive. If the stroke cannot be classified into a primitive he breaks the stroke from the point of highest curvature and recursively tries to classify the sub strokes.

For line segment approximation he tries to fit the gradient graph of the stroke to a horizontal and the line to a straight line from the endpoints. For circles the direction graphs should be constant and increasing so he tries to fit the gradient graph with a straight line.

For self intersecting strokes such as helix its not a good methodology to break the stroke from the point of highest curvature so here the author uses a different methodology. He breaks the stroke from the point of highest curvature as well as from the point of intersection and then tries to classify the sub strokes. The result from both sub strokes is obtained and analyzed which one to chose. Here the author follows the strategy of 'simpler is better'. That stroke classified as a circle is preferred over the sub stroke classified as a set of lines etc.

Author then uses some post processing to clean up the stroke for beautification and basic object recognition into square, circle and rectangles etc.

The author claims to have achieved an accuracy rate of 98% for polylines and 94% for arcs.

Discussion

The paper presents good ideas for domain independent object recognition. The author explains the process of basic object recognition quite vaguely about how he uses his algorithm for basic object recognition.

Although it shows some new techniques for stroke approximation but I would still prefer PaleoSketch over it because it explains in detail about each process and does some very similar work.