3D Point-cloud Segmentation System Based on AI Model

With the rapid development of technology, big data, Internet of Things, and deep learning technologies are gradually developing, among which the development of 2-D image recognition in deep learning is becoming more and more mature. For these reasons, the image recognition of 3D point-cloud is still under development. We combine projection and point-cloud algorithms for large scale semantic segmentation of 3D point-cloud images, and then combine the new neural network based on "Local Flattening for Point Convolution" and "Random Sampling Network" to lighten the model by using depth-separable convolution and quantization. Finally, we implement the convolutional layers in the neural network based on a digital integrated circuit design flow based on a standard cell library.