Chapter 5. Tracking Visually Salient Objects

The goal of this chapter is to track multiple visually salient objects in a video sequence at once. Instead of labeling the objects of interest in the video ourselves, we will let the algorithm decide which regions of a video frame are worth tracking.

We have previously learned how to detect simple objects of interest (such as a human hand) in tightly controlled scenarios or how to infer geometrical features of a visual scene from camera motion. In this chapter, we ask what we can learn about a visual scene by looking at the image statistics of a large number of frames. By analyzing the Fourier spectrum of natural images we will build a saliency map, which allows us to label certain statistically interesting ...

Get OpenCV with Python Blueprints now with O’Reilly online learning.

O’Reilly members experience live online training, plus books, videos, and digital content from 200+ publishers.