In the widely cited paper “Rapid object detection using a boosted cascade of simple features“, Viola and Jones (CVPR 2001) apply “Harr-like” features and AdaBoost to a fast “cascade” of increasingly complex image classifiers (mostly facial recognition). They write, “The cascade can be viewed as an object specific focus-of-attention mechanism which unlike previous approaches provides statistical guarantees that discarded regions are unlikely to contain the object of interest.” The Harr-like decomposition quickly (constant time) creates mostly localized features and AdaBoost learns quickly so the combination is fast. They report, “In the domain of face detection it is possible to achieve fewer than 1% false negatives and 40% false positives using a classifier constructed from two Harr-like features.” [emphasis added]