We have previously studied how to describe objects by means of key points and features, and how to find the correspondence points in two different images of the same physical object. However, our previous approaches were rather limited when it came to recognizing objects in real-world settings and assigning them to conceptual categories. For example, in Chapter 2, Hand Gesture Recognition Using a Kinect Depth Sensor, the required object in the image was a hand, and it had to be nicely placed in the center of the screen. Wouldn't it be nice if we could remove these restrictions?
The goal of this chapter is to train a multiclass classifier to recognize traffic signs. In this chapter, we will cover the following concepts:
- Planning the app
- Briefing on supervised learning concepts
- Understanding the German Traffic Sign Recognition Benchmark...
