Neural network point cloud data analyzing method and computer program product

A neural network point cloud data analyzing method, comprising:

• a data input step, wherein a processor receives a point cloud data;
• and
• an analyzing step, wherein the processor analyzes the point cloud data based on an enhanced VoxNet 3D model, and the enhanced VoxNet 3D model comprises:
• an input layer for inputting the point cloud data;
• a first hidden unit signally connected to the input layer and comprising a first convolution layer, a first batch-normalization layer and a first activation layer in order;
• a first pooling layer receiving an output from the first activation layer;
• a 1st to a 3rd second hidden units sequentially connected after the first pooling layer, each of the 1st to the 3rd second hidden units comprising a second convolution layer, a second batch-normalization layer, a second activation layer, a third convolution layer, a third batch-normalization layer, an adding layer and a third activation layer in order, wherein the adding layer receives and summarizes an output from the second batch-normalization layer and an output from the third batch-normalization layer;
• a second pooling layer connected between the third activation layer of the 1 st second hidden unit and the second convolution layer of a 2nd second hidden unit of the 1st to the 3rd second hidden units;
• a third pooling layer connected between the third activation layer of the 2nd second hidden unit and the second convolution layer of the 3rd second hidden unit;
• and
• a fourth pooling layer connected after the third activation layer of the 3rd second hidden unit.