Reading #15: An Image-Based Trainable Symbol Recognizer for Sketch-Based Interfaces

Comments:
JJ

Summary:
Image-based recognition with only a single provided template. Such is the boast of the system designed by Kara and Stahovich. This paper also outlines the unique and low-cost polar coordinate analysis which is used to achieve rotation invariance. A three step process that begins with rotational checks is used to prune possible templates for any given sketch. Each sketch is treated as a 48x48 bitmap image which preserves the input's aspect ratio. Template matching is then carried out through the use of four different techniques. Results of these four techniques are then "parallelized" and "normalized", resulting in values between 0 and 1 which are used to determine how close an input sketch is to the different templates. Through a series of tests, the authors proved that their system was able to recognize the sketches of amateurs using only one or two templates with an accuracy of over 90%.

Discussion:
Though I brushed over it in the summary, a great new idea coming out of this paper is the polar transformation used to handle rotations. It is very constricting to require users to always draw with the exact same rotation. You could always create templates for different rotations of the same gesture... but why waste the time when you can use something as efficient as the transformer presented here?