SURF is an improvement over traditional feature detection algorithms, designed to be faster while still maintaining robustness. Similar to SIFT, SURF detects and describes local features in images. It is invariant to changes in scale, rotation, and illumination to a certain extent. SURF uses integral images for fast computation, which makes it suitable for real-time applications such as augmented reality, where quick feature extraction and matching are required. It has been applied in areas like tracking moving objects in video streams and registering multiple images for panoramic image creation.
