Method for positioning three-dimensional human body joints in monocular color videos

The invention provides a method for positioning three-dimensional human body joints in monocular color videos. The method comprises the following steps of: S1, constructing a configurable depth model and importing time sequence information in the depth model; S2, collecting training samples and learning parameters of the depth model by utilizing the training samples; and S3, initializing the depth model by utilizing the parameters learnt in S2, and converting monocular color video data needing three-dimensional human body joint positioning into a plurality of frames of continuous two-dimensional images, inputting the images into the depth model to carry out analysis, and aiming at each frame of two-dimensional image, outputting three-dimensional human body joint coordinates of figures in the image. According to the method, a deep-level convolutional neural network is constructed by utilizing deep learning so as to automatically learn effective spatial-temporal features from a lot of training samples without d