Three-dimensional face feature point positioning method based on noise reduction self-coding network

The invention discloses a three-dimensional face feature point positioning method based on a noise reduction self-coding network. The method comprises the following implementation steps: extracting anose tip point coordinate from a messy face point cloud; extracting a human face region through the position of the nose tip point and preprocessing the human face region; and training a face model, carrying out manual region segmentation on the face by the model, and dividing the to-be-detected face into a plurality of regions according to the segmented face and a rigid matching algorithm; performing shielding detection on each region, and converting the shielding degree into coefficient representation; training a noise reduction auto-encoder for each divided shielding area, wherein each noise reduction auto-encoder outputs a feature point positioning result; fusing the positioning results of the plurality of feature points through the shielding coefficient to obtain a final result, and finishing the whole fixed