Summary
In this chapter, we explored a way to label the potentially interesting objects in a visual scene, even if their shape and number is unknown. We explored natural image statistics using Fourier analysis, and implemented a state-of-the-art method for extracting the visually salient regions in the natural scenes. Furthermore, we combined the output of the salience detector with a tracking algorithm to track multiple objects of unknown shape and number in a video sequence of a soccer game.
It would now be possible to extend our algorithm to feature more complicated feature descriptions of proto-objects. In fact, mean-shift tracking might fail when the objects rapidly change size, as would be the case if an object of interest were to come straight ...
Get OpenCV: Computer Vision Projects with Python now with the O’Reilly learning platform.
O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.
