We have already commented on the accuracy of center agreement among volunteers when looking at all the classifications through the entire time interval. Now we can see how our volunteers match up for a single frame. Five sample frames were pulled out and classified by about 10 individuals.
The centers of these classifications were visualized and passed by the clustering algorithm that every frame will go through. These centers and clusters for one of the sample frames are given below (the black dots for the clusters refer to noise).
What was also interesting to look at were all the drawn ellipses for a frame. It can be seen that the points that are considered noise also deviate considerably in size along with distance from neighboring centers, which is common among other frames as well. The comparable size and orientation of a certain antinode region among volunteers now opens the possibility to effectively analyze these attributes throughout the time interval. As we gain more classifications, a more coherent picture of what each antinode region looks like through time will be made available! More ellipse plots can be seen below and keep up the great work everybody!