bahadir's profile - activity

Hello,

Currently i am developing a pedestrian counter project using OpenCV+QT on linux. My idea about this process is;

1. Capture Frames.

2. Do Background Subtraction.

3. Clear noises (erode, dilate).

4. Find blobs (cvBlobslib) - foreground objects.

5. For each blob, set ROI and search for pedestrians (LBP with detectMultiScale) in these blobs (for better performance).

6. For each found pedestrian do a nested upper body search(Not sure) (better reliability).

7. If same pedestrian is found on continuing frames (3-4 frames maybe) - add that area to camshift and track - mark as pedestrian.

8. Exclude camshift tracked areas from blob detection for next frames.

9. If a pedestrian crosses a line increment number.

I want to know if i am on the right track. Do you have any suggestions for this task, or do you think some other ways are better than mine, or are there unnecessary steps in my algorithm?