Reading 26: Envisioning sketch recognition: a local feature based approach to recognizing informal sketches

Citation

Oltmans, Michael. Envisioning sketch recognition: a local feature based approach to recognizing informal sketches. Diss. Massachusetts Institute of Technology, 2007.

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Summary

This thesis presents a novel way to recognize sketches not by their geometric features but by introducing a new type of features named the bullseye feature by the authors. The idea is overlay the input sketch on a bullseye concentric circles shape and count the number of dots in each part of the shape. Then match shapes by finding how close are the number of points in each of the bullseye part. The bullseye features look like these:

The bullseye feature typically is the number of ink points lying in each of the part of the bullseye. The radius of the concentric circles increases on a log scale. The inner parts are smaller and the outer parts are larger, the intuition behind which is central parts of a sketch are much more important than the outer parts.

Discussion

By calculating the bullseye's histogram relative to the stroke direction, instead of relative to the x-axis, the bullseyes are rotationally invariant and do not change when the shape is drawn at a different orientation.

Each part is also divided into 4 sub-bins containing number of points at particular stroke angle. Doing this encodes some sense of direction in the bullseye features. The bins look like this:

The distance metric used to find the close ness of two bullseye features is weighted such that inner circles are weighted higher than the outer circles, thereby complementing the larger size of the outer bins. The distance metric is a modified version of the common X square distance. 

The shapes are represented in the form of Match Vectors in the Codebook.