The invention relates to a
pedestrian detection and recognition method based on a
deep learning cascade neural network, and the method comprises the steps: (1) sending a preprocessed
video image sequence to a first-level neural network, and obtaining the original information of a
pedestrian in an image; (2) segmenting a local image of the
pedestrian in the image and carrying out normalization
processing to construct a
pedestrian recognition data set; and (3) sending the
pedestrian recognition data set to a second-level neural network, and extracting feature information of the pedestrians to realize
identity recognition of the pedestrians. According to the method, the problems of inaccurate target positioning, low pedestrian resolution, low pedestrian
identity recognition accuracy and the like in the image are solved, relatively
good image information of the target pedestrian can be obtained, and the
pedestrian detection and recognition accuracy is improved. The method is good in
practice effect and high in operation speed, detection and
identity recognition of the target pedestrian can be rapidly and accurately achieved in real time, and the method is suitable for various fields ofvideo monitoring, intelligent communities, specific place supervision and the like.