MARQS

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Summary

This paper discusses an algorithm that can identify multiple stroke sketches using a set of global features that are both domain and style independent. To give a real world example the author have created an application called MARQS. In this application the user can store photo and music albums, which can be retrieved by matching multi-stroke sketches which the user designated during album creation.
Recognition algorithm uses two different classifiers depending upon the the number of training examples available. Initially the user is asked to give only one example sketch and whenever the user performs a search the sketch he gave he gave for searching is also added to examples. The algorithm uses global features for the sketches since it puts no constraint on the users on how they would draw the sketches. Currently it uses four global features to describe a sketch. 1) Bounding box aspect ratio: the total width of the sketch divided by the total height of the sketch. 2) Pixel density: the ratio of the filled (black) pixels to total pixels within the sketch’s bounding box. 3) Average curvature: the sum of the curvature values of all the points in all strokes divided by the total sketch length (sum of the stroke lengths of all strokes in the sketch). 4) The number of perceived corners across all strokes of the sketch.
MARQS is real world application which utilizes the the recognition algorithm mentioned above. It’s a media storage and retrieval query sketch system. It allows users to create, edit, open, add and delete albums and pictures. It also allows user to search for an album through a sketch and gives the top 4 sketches that matched.
To gather the preliminary data 1350 different sketch queries were performed (15 sketches, 9 queries each, 10 tests). The system used the single classifier 27% of the time and linear classifier 73% of the time. 70% of the time the system produced top result and 98% in the top 4. 2% of the time the results were not in top 4.

Discussion
Here I liked the idea of the system becoming more accurate with every search performed. The idea of adding the query sketch to example space is good. But I am not sure that its a good enough algorithm for other real world application like drawing a circuit diagram.
In MARQS the application shows top 4 results and then the person chooses one from it which tells the system to associate that query sketch to a particular example class. By using MARQS the person is training the system without actually knowing that he is training the system.

I also think 70% accuracy for top result will not be very effective in real world applications. Nonetheless this system opens a new dimension of multi-stroke recognition