Real time motion segmentation

Motion segmentation is one of the greatest challenges in computer vision. Accurate real time segmentation is difficult to achieve with ordinary camera. Using 3D camera we will get much better approximation .but 3D camera is costly.

i had done edge based motion detection , now i just did chain method of clustering on the edges to group the edges in to different groups. Its not accurate yet. with ordinary 2d camera it is difficult to cluster objects due to the perspective effect. But it can give better results if we could place the camera in somewhat higher position compared the the objects.

see the videos here.. ( edges in a group have same colors )

Updated motion segmentation , see the results in video below. I need to remove the noisy segments. Noise segments are created due to the illumination changes. Hopes it can be done with some pixel modeling schemes.

Boundary Approximation

I have been playing with snakes( aka active contours ) for a quite long time.
Basic snake is not able to detect boundary correctly. But it is very fast.

I tried to extend the gradient vector field of the image using Laplace equation. it works. But it takes a few seconds to generate the vector field.. :( , now i am thinking about using distance transform to generate the vector field.

See the video below to see snake in action.