Aiming at the problem that the aggregate channel feature（ ACF） does not adequately describe human contour features in human detection

a Haar-Like feature based on prior knowledge is used to enhance the ability of the detector to describe human contour features. A set of Haar-Like features is designed. This feature takes advantage of prior knowledge of the human body’s upper body contour characteristics and treats the head

upper body

and background as three different parts. The experimental results show that compared with the ACF and other algorithms

the detection method combined with the Haar-Like feature can improve the detection precision of the detector

and the recall rate is increased to 94. 57 % on the INRIA data set.