Hand detection

Initially when there is no hand the tracker will be in a steady state with all particles being randomly spread across the image, giving an estimation of the location of the object at the centre of the image, roughly. However, we cannot use this estimation because there is no actual hand. The problem we are presented is therefore about detecting when the hand comes into scene.

Using the median of densities

Let the probability densities be measured as the Mahalanobis distance from the colour of a pixel to the mean colour of a skin pixel. At first, the median of the probability densities at each pixel within an 8x8 window centered at the estimated location was used to determine if a hand was in place. The reason behind this approach was that if the median was evaluated as 'skin' then most pixels within the window would be 'skin' and hence a hand was in place.

This method worked intermitently since the tracker was not able to follow the hand with a high enough precision when it was moved at varying speeds and directions. The moved hand would cause the median of the window to change drastically when the estimation was close to an edge of the hand.

Using the standard deviation

Another method tried was using the standard deviation of the particles. An assumption was made that if it was below a certain threshold then a hand was detected.

This method proved to be very robust even though it still had a weakness. If the noise in the image was not properly removed the tracker could be following wrong objects and thus mistakenly detecting a hand.

Motion detection

To start the tracker a basic motion detection of the hand could be used. However, one could argue that some automatism and convenience is lost.