US Patent Application 17900198. METHOD FOR ANALYZING SHAPE OF OBJECT AND DEVICE FOR TRACKING OBJECT WITH LIDAR simplified abstract
METHOD FOR ANALYZING SHAPE OF OBJECT AND DEVICE FOR TRACKING OBJECT WITH LIDAR
Organization Name
Inventor(s)
METHOD FOR ANALYZING SHAPE OF OBJECT AND DEVICE FOR TRACKING OBJECT WITH LIDAR - A simplified explanation of the abstract
This abstract first appeared for US patent application 17900198 titled 'METHOD FOR ANALYZING SHAPE OF OBJECT AND DEVICE FOR TRACKING OBJECT WITH LIDAR
Simplified Explanation
The present disclosure describes a method and device for analyzing the shape of an object using LiDAR technology. LiDAR is a remote sensing method that uses laser light to measure distances and create detailed 3D maps of objects and environments.
- LiDAR points are obtained from multiple layers of the object using LiDAR technology.
- A shape flag is determined for each layer based on the LiDAR points present on it, using predetermined shape types.
- A confidence score is calculated for each shape flag, based on the LiDAR points used in its determination.
- The shape flag of the object is determined by considering the shape flags and confidence scores from all the layers.
This method allows for accurate analysis and tracking of an object's shape using LiDAR technology.
Original Abstract Submitted
The present disclosure relates to a method of analyzing a shape of an object and a device for tracking an object with LiDAR. A method for analyzing a shape of an object by use of LiDAR, according to an embodiment of the present disclosure, comprises obtaining a plurality of layers of LiDAR points for the object by use of the LiDAR, determining a shape flag for each of the layers by use of at least a part of LiDAR points thereon according to a plurality of predetermined shape types, calculating a confidence score for the shape flag determined for each of the layers by use of the at least part of LiDAR points; and determining a shape flag of the object by use of the shape flags determined for the plurality of layers and the confidence scores.
