23,181 iterations of testing

Posted: February 7, 2009 at 8:04 pm

After doing a full days testing on the camera motivation, I think things are close. In order to keep the camera from getting too lost in the small details, I’ve increased the multiplier (not the offset) for each step. The result is that areas of focus are quite large. Additionally I’ve added a reset so that when the motivation takes the camera to the edge of the visual field, a random pan/tilt is generated. This allows the path of the camera to search over the whole space with much better coverage. Out of the 23,181 iterations the camera motivation was reset 2394 times, representing only 10% of the camera movements. Although the goal was to remove the random aspect of the camera I’m quite happy with this direction. Perhaps another idea will come up in the future to remove this random requirement. For example the camera could be reset to the centre of the least dense area. This would require a much more complex statistical analysis of its motivational behaviour.

Here is a plot of the motivation paths of the camera during this test. The random movements have been removed.

pantilt10.png

As usual, the movements start in red and end in green.

Here is a 2D histogram of the density of the data. Notice the coverage over the visual field.

pantilt10-hist2d-zoom.png

Here is the histogram overlayed over the visual field. Areas that are white are not visited often, areas that are visible are often visited (higher density).

pantilt10-hist2d-overlay.jpg

The next step is to capture images from each location and see how the SOM responds to the non-uniformity. It seems clear the visible areas above (houses, trees) will take up much of the SOM, where other areas may not be represented (sky, grass).