3D enhanced face recognition based on point cloud and RGB
To solve the problem of low recognition rate due to the fact that the depth information of face images cannot be obtained by ordinary cameras,a 3D face enhancement recognition method based on point cloud and RGB images is proposed.Firstly,the depth camera is used to collect point cloud data and RGB images,and the attention mechanism of Transformer is utilized to establish the image fusion mechanism.Secondly,the encoder network layer,i.e.,PointTransformer,is added to the Mobilenet of Facenet,which can be realized to divide the data into multiple pieces for calculation.In the encoder network,the attention mechanism is utilized to fuse point cloud with RGB image to enhance the accuracy of 3D face recognition.The simulation results show that the accuracy of the 3D face enhancement recognition method based on point cloud and RGB image is 99.67％,which verifies the feasibility of this method.
three-dimensional face point cloudface recognitiontransformerattention mechanismfeature fusion
万方数据
维普
