Reading 5#: Gestures without Libraries, Toolkits or Training: A $1 Recognizer for User Interface Prototypes

Comments:
Wenzhe Li
Summary:
The paper introduces a fast, easy and accurate recognizer for unistroke gestures, which enable novice programmers to incorporate into UI.

Several advantages of $1 are described, such as
1.resilience to variation in sampling
2.rotation, scale and position variance
3.teach new gestures with only 1 gesture
4.more accurate than DTW and Rubine
while disadvantages are
1. cannot distinguish gestures whose identities depend on specific orientation
2. cannot distinguish gestures whose identities depend on speed

$1 consists of 4 steps:
1. resample the point path to form a fixed number of equidistantly spaced points
2. rotate based on indicative angle, which is the angle between the first point and the centroid point.
3. scale to a square and translate the centroid to the original point.
4. find the optimal angle for the best score.

Finally, the author makes comparison among $1, DTW and Rubine.
1. $1 and DTW are significantly more accurate than Rubine.
2. $1 and DTW improve very slightly by the increase of the number of training examples, while Rubine a lot.
3. All three are affected similarly by the articulation speed.
4. $1 has the best falloff, DTW second, and Rubine third.
5. $1 has the fastest speed, Rubine second, and DTW third.

Discussion:
Is $1 really better than others? Probably not. $1 is only better in the dataset described in the paper. Different recognizers for different datasets. Any algorithm can be the best one if your want. The author spend 2 pages on demonstrating the advantage of $1, which seems useless.

However, I still appreciate $1, due to its easiness and fast speed. It is suitable to novice programmers, especially those who are not familiar with sketch recognition. In this view, $1 is a great work.