Point cloud analysis has found its application in indoor scene understanding and more recently has become an essential component of outdoor applications. This is due to the increasing availability and affordability of 3D sensors such as LiDAR. Visualizing the point cloud data in 3D viewer andlabeled for more precise detection and classification for right dimensions and tracking label at high accuracy.
A 3D boxes for better object detection and tracking including the every points with high accuracy to get the details like size, location, yaw, speed, pitch with class. We use highly advanced 3D point cloud annotation tool to annotate all kind of objects and assign particular classification with extra attributes .
Semantic segmentation of 3D point cloud data where each point is assigned with a semantic class, has recently gained tremendous attention from data mining researchers and industrial practitioners. Accurate 3D-segmentation results can be used for constructing 3D scene for robotic navigation, autonomous driving and so on.
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