Distributed Averages of Gradients (DAG): A Fast Alternative for Histogram of Oriented Gradients

We propose a compact descriptor for the purpose of dense image matching and object recognition. The descriptor is calculated based on local gradients about each point in an image. It contains the averages of gradients at four different windows surrounding a center point. The descriptor is calculated much faster than histogram of oriented gradients (HOG). Additionally, it will be shown that it is more discriminative than HOG. We used the new descriptor for two applications needed in RoboCup competitions very often. First, computation of dense optical flows and 3D scene reconstruction from two views. Second, human face detection.