Efficient LiDAR data compression for embedded V2I or V2V data handling
This addresses the challenge of handling large LiDAR data volumes in intelligent vehicles and transportation systems, though it appears incremental as it builds on existing compression methods.
The paper tackles the problem of compressing LiDAR data for storage and transmission in vehicle-to-vehicle or vehicle-to-infrastructure applications, presenting a method that achieves efficient compression while being designed for embedded systems with low processing power.
LiDAR are increasingly being used in intelligent vehicles (IV) or intelligent transportation systems (ITS). Storage and transmission of data generated by LiDAR sensors are one of the most challenging aspects of their deployment. In this paper we present a method that can be used to efficiently compress LiDAR data in order to facilitate storage and transmission in V2V or V2I applications. This method can be used to perform lossless or lossy compression and is specifically designed for embedded applications with low processing power. This method is also designed to be easily applicable to existing processing chains by keeping the structure of the data stream intact. We benchmarked our method using several publicly available datasets and compared it with state-of-the-art LiDAR data compression methods from the literature.