Harris Corner Detection is a popular technique in computer vision used to identify corners or interest points in images. It works by analyzing the intensity changes in a small window around each pixel, determining where significant changes occur in multiple directions. This helps to locate points that are stable and can be reliably tracked across different images. The method uses a mathematical approach based on the Harris matrix, which calculates the gradient of the image. By applying a threshold to the response function, it distinguishes between corner points and other features, making it useful for tasks like image matching and object recognition.