Disclosed are a joint modeling method and apparatus for enhancing local features of pedestrians. The method includes the following steps: S1: acquiring an original surveillance video image data set, dividing the original surveillance video image data set into a training set and a test set in proportion; S2: cutting the surveillance video image training set to obtain image block vector sequences. In the present disclosure, local features of pedestrians in video images are extracted by a multi-head attention neural network, weight parameters of image channels are learned by channel convolution kernels, spatial features on the images are scanned through spatial convolution, local features of pedestrians are enhanced to improve the recognition rate of pedestrians, a feed-forward neural network and an activation function are adopted, so as to realize pedestrian re-recognition, thereby obtaining face images available.