Scale Invariant Feature Transform (SIFT)
Even though corner features are "interesting", they are not good enough to characterize the truly interesting parts. When we talk about image content analysis, we want the image signature to be invariant to things such as scale, rotation, illumination, and so on. Humans are very good at these things. Even if I show you an image of an apple upside down that's dimmed, you will still recognize it. If I show you a really enlarged version of that image, you will still recognize it. We want our image recognition systems to be able to do the same.
Let's consider the corner features. If you enlarge an image, a corner might stop being a corner as shown below.
In the second case, the detector will not pick up this ...