Comment Location:
http://martysimpossibletorememberurl.blogspot.com/2010/10/reading-12-constellation-models.html
Summary:
The paper takes a new twist on recognition by using constellation shapes as basis for shape recognition. Remarkably, it demonstrates some success when recognizing crude facial sketches. It relies on the connectivity between the shapes in the facial sketch. The recognition algorithm may be called a constellation model, but it's really a graph-type recognition algoirthm. Strokes/individual shapes form a node, and the connection between the nodes are used as part of the recognition algorithm. I won't go into the specifics of the algorithm.
For evaluation, the author used 5 classes of objects with 7–15 labels each. They have been tested on drawings having 3–200 strokes. The author used 20-60 training examples for each class. The algorithm's major weakness was its computation time. It took over an hour to recognize a face.
Discussion:
This paper takes an...intersting...approach. Truthfully, I would never have considered using constellation shapes as part of ANY recognition system; the thought never occurred to me. I wonder if this will be of any help in the 2nd homework assingment...If anyone has any ideas regarding this, please share. The author demonstrated (some) success in recognizing complex shapes.
I must admit, the numbers for evaluation (3-200 strokes in a drawing) were impressive. The computation time is a problem, but the algorithm recognized complex shapes such as sailboats and faces.
I guess it will provide some kind of help in Project2. The constellation model can be used to construct each symbol in the project. Each symbol can be divided into mandatory parts and optional parts as the paper says.
ReplyDeleteThe number is impressive, but there is no recognition rate in the paper. Anything can recognize sketches, but what we are concerned about is the accuracy rather than the capability.