You can run your video through a motion detection & tracking process using python & OpenCV as in this tutorial.
- Both are Free, Gratis & Open Source.
- Both are cross platform and will run on Windows, OS-X, Linux or even Raspberry Pi platforms.
- The referenced tutorial uses just 90 lines of code & no compiler.
The tutorial does not give an output of the times that the event(s) occurred but if you use:
# Find OpenCV version
(major_ver, minor_ver, subminor_ver) = (cv2.__version__).split('.')
if int(major_ver) < 3 :
fps = camera.get(cv2.cv.CV_CAP_PROP_FPS){0}".format(fps)
else :
fps = camera.get(cv2.CAP_PROP_FPS)
Note that I have used camera in the above to agree with the tutorial but getting fps will not work from an actual web camera see here.
Used once the file is opened to get the frames per second and then simply keep a count of the frames processed you can then compute the time point within the video and print that out with an appropriate message, and/or save it to a text file, whenever the status changes to occupied or unoccupied.