OpenCV: Computer Vision Projects with Python

Summary

In this chapter, we learned about object tracking. We learned how to get motion information using frame differencing, and how it can be limiting when we want to track different types of objects. We learned about colorspacethresholding and how it can be used to track colored objects. We discussed clustering techniques for object tracking and how we can build an interactive object tracker using the CAMShift algorithm. We discussed how to track features in a video and how we can use optical flow to achieve the same. We learned about background subtraction and how it can be used for video surveillance.

In the next chapter, we are going to discuss object recognition, and how we can build a visual search engine.