Landmark Detection

In Object Localization we saw how we can get a neural network to output 4 numbers: \(b_x, b_y ,b_h, b_w\) to specify the bounding box of an object we want to localize. In more general cases we can have a neural network which outputs just \(x\) and \(y\) coordinates of important points in the image, sometimes called landmarks.

Let’s see a few examples. Let’s say we’re building a face recognition application, and for some reason we want the algorithm to tell us where is the corner of someone’s eye.

References

• http://datahacker.rs/deep-learning-landmark-detection/