Gestures without libraries, toolkits or training: a $1 recognizer for user interface prototypes

Paper
Wobbrock, Jacob O., Andrew D. Wilson, and Yang Li. "Gestures without libraries, toolkits or training: a $1 recognizer for user interface prototypes." Proceedings of the 20th annual ACM symposium on User interface software and technology. ACM, 2007.
Publication Link: http://dl.acm.org/citation.cfm?id=1294238

Summary

The $1 recognizer paper describes a 'simple' template matching algorithm that handles scaling, rotation and translation. The authors describe the algorithm, along with implementation details. They also compare their algorithm with two other well known algorithms used in gesture recogniton (Rubine, and dynamic time warping).  

Discussion

Pros

It is a simple algorithm to implement.
The heuristic approach to reducing the iterations for rotation alignment was very creating and interesting. 

Cons.

The paper was difficult to follow. 
I would like to know if their heuristic for rotation and alignment has some theoretical grounding in psychology. Do people tend to draw or start a drawing based on some mental orientation or projection of the object? Maybe I missed the motivation behind this heuristic but I feel it is a key contribution that should have been better highlighted.
It's simplicity makes it very limited in its capability. I suspect that the size of the 'template' library will grow significantly given its high sensitivity to variation in shapes.

I'd also like to see the running time for this algorithm and how it compares with others.