학술논문

Point-Cloud Perspective Transform via Super-Resolution Model
Document Type
Conference
Source
2022 IEEE International Conference on Consumer Electronics-Asia (ICCE-Asia) Consumer Electronics-Asia (ICCE-Asia), 2022 IEEE International Conference on. :1-4 Oct, 2022
Subject
Aerospace
Communication, Networking and Broadcast Technologies
Computing and Processing
Engineering Profession
Fields, Waves and Electromagnetics
Geoscience
Photonics and Electrooptics
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Point cloud compression
Laser radar
Three-dimensional displays
Shape
Superresolution
Transforms
Object detection
Super-resolution
ML
AI
Point-cloud
Language
Abstract
The LiDAR sensor, which detects the relative distance to an object, is widely used in the field of 3D object detection based on point cloud, and is a key sensor in autonomous vehicles because it can recognize the distance and shape of the surrounding object. The LiDAR sensor extracts different features even when looking at the same object depending on the installation location and angle. Usually, the open dataset and the user's LiDAR installation location are different. In this case, the performance of the model trained with the open dataset is not fully exhibited. We propose a method and model to convert the point cloud data acquired from the source location to the point cloud acquired from the target location.