Method and device for pedestrian detection based on depth convolutional network

The invention discloses a method and a device for pedestrian detection based on a depth convolutional network. The method comprises a convolutional neural network training step and a pedestrian detection step. The convolutional neural network training comprises the following steps: S10, a plurality of groups of sample image data are selected from an image library; S11, one group of sample image data is sent to an input layer of a multilayer neural convolutional network; S12, the output vector of an intermediate layer of the neural convolutional network and the actual output vector of an output layer are calculated to obtain the error of the intermediate layer and the error of the output layer; S13, the weight from an output layer vector element to an intermediate layer output vector element and the weight from the intermediate layer output vector element to the output layer vector element are adjusted; and S14, the total error function value is judged, and pedestrians are detected by use of the trained networ