Learning OpenCV 3 Computer Vision with Python - Second Edition

Summary

This chapter explored the vast and complex topic of video analysis and tracking objects.

We learned about video background subtraction with a basic motion detection technique that calculates frame differences, and then moved to more complex and efficient tools such as BackgroundSubtractor.

We then explored two very important video analysis algorithms: Meanshift and CAMShift. In the course of this, we talked in detail about color histograms and back projections. We also familiarized ourselves with the Kalman filter, and its usefulness in a computer vision context. Finally, we put all our knowledge together in a sample surveillance application, which tracks moving objects in a video.

Now that our foundation in OpenCV and machine learning is ...