I finished the width/height ratio normalisation, and then I did the t-test to compare the new normal and stress results. There are no significant differences between them, with p-value (two-tail) > 0.05. Although this feature fails to be a good feature, I learnt a lot from the normalisation process. What is more, I think this idea can be used in the future analysis as well, because the differences between letters may also have other impacts on the gestures.
Tuesday, 12 June 2012
After discussing with my supervisor, he suggest me to normalise the width/height ratio for different letters, so that it can eliminate the effect of the generic shape of the letter. Then, I will explore more about the bounding box, to understand it in more details and compare my results with the experimenter's results.
In the further analysis, I need to use the actual written letter to group gestures, instead of the automatic recognition, so I need another field in the Stroke called "written". Since I have already summarised all the recognition errors, I will use the list to correct recognition result for each gesture.
Friday, 8 June 2012
I would like to start the analysis from an easy and straightforward feature -- bounding box. First of all, this week I wrote some scripts to abstract bounding box information from processed data (one file for each subject), like the width, height, and width over height ratios. Then, I computed average values for different sessions (Normal and High). I will use t-test to compare two groups of results.
However, there are some issues I want to discuss with the supervisor. The most important one is the letter's shape has significant effect on the bounding box, and I am not sure whether I can compare the result. Additionally, I am not sure how to deal with slant, which the stoke is not vertical to the plane, because slant stroke will change the dimension of bounding box.