In this chapter, we covered a wide range of concepts and techniques, including HOG, BoW, SVMs, image pyramids, sliding windows, and NMS. We learned that these techniques have applications in object detection, as well as other fields. We wrote a script that combined most of these techniques – BoW, SVMs, an image pyramid, a sliding window, and NMS – and we gained practical experience in machine learning through the exercise of training and testing a custom detector. Finally, we demonstrated that we can detect cars!
Our new knowledge forms the foundation of the next chapter, in which we will utilize object detection and classification techniques on sequences of frames in videos. We will learn how to track objects and retain information about them – an important objective in many real-world applications.