Summary

This chapter described the role of OpenCV and CUDA in real-time object detection and tracking applications. It started with the introduction of object detection and tracking, along with challenges encountered in that process and the applications of it. Different features like color, shape, histograms, and other distinct key-points, like corners, can be used to detect and track objects in an image. Color-based object detection is easier to implement, but it requires that the object should have a distinct color from the background. For shape-based object detection, the Canny edge detection technique has been described to detect edges, and Hough transform has been described for straight line and circle detection. It has many applications, such as land detection, ball tracking, and so on. The color and shape are global features, which are easier to compute and require less...