Suggestions for improvenent object detection

Question

I am new to opencv and i am trying to track some moving objects(e.g. cars) in an image. I have computed the optical flow and have used it to implement kmeans and try something like background substraction , i mean seperate moving objects from stationary. Then i have also used the intensity of the video as information . The following screenshots are from the result of the flow and the k means segmentation respectively :

The results are not good but also not bad. How could i proceed from now on ? I am thinking of trying SURF feature extraction and SURF detector . Any ideas are welcome .

Answer 1

It seems you are using dense optical flow. I would advice trying some feature detection (surf, fast, whatever) followed by sparse optical flow tracking(from my experience it is better than feature matching for this task). Then, once you have the feature correspondences over some frames, you can use fundamental matrix, trifocal tensor, plane+parallax or some other method to detect moving objects. You can later cluster moving objects into different motion groups that represent different objects.

Also it seems that your camera is fixed. In this case you can drop the movement detection step, and consider only tracks with enough displacement, and then do the clustering into motion groups.