Patent ID: 11875424
Assignee: SHENZHEN UNIVERSITY
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 1:
2. The point cloud data processing method according to claim 1, wherein the number of Hausdorff convolutional layers in the encoder is not less than two; and the calculating a convolution of the neighboring point set with the distance matrix and the network weight matrix in the Hausdorff convolution layer in the encoder to obtain the high-dimensional point cloud features comprises:
in a process of calculating convolution in a first Hausdorff convolution layer, convolving the neighboring point set, which is used as input features, with the distance matrix and the network weight matrix, to obtain output features; and
in a non-first Hausdorff convolutional layer, convolving output features of a previous Hausdorff convolutional layer of a current non-first Hausdorff convolutional layer, which are used as input features of the current non-first Hausdorff convolutional layer, with the distance matrix and the network weight matrix, to obtain output features, and if the current non-first Hausdorff convolutional layer is a last Hausdorff convolutional layer, using output features of the last Hausdorff convolution layer as the high-dimensional point cloud features.