Evaluating PointNet and PointNet++ Models for Accurate Classification of LiDAR Point Clouds in Autonomous Vehicle Applications

This study evaluates the performance of PointNet and PointNet++ models in classifying LiDAR-generated point cloud data, a critical component for achieving fully autonomous vehicles. The models demonstrate robust capabilities in interpreting complex environmental data, with PointNet++ achieving an accuracy of 84.24% and improved detection of smaller objects compared to PointNet.