A Survey on Data Compression Techniques for Automotive LiDAR Point Clouds

A Survey on Data Compression Techniques for Automotive LiDAR Point Clouds

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In the evolving landscape of autonomous 100% Human Hair Full Wigs driving technology, Light Detection and Ranging (LiDAR) sensors have emerged as a pivotal instrument for enhancing environmental perception.They can offer precise, high-resolution, real-time 3D representations around a vehicle, and the ability for long-range measurements under low-light conditions.However, these advantages come at the cost of the large volume of data generated by the sensor, leading to several challenges in transmission, processing, and storage operations, which can be currently mitigated by employing data compression techniques to the point cloud.This article presents a survey of existing methods used to White Crystal Mid Rise Wrap Skirt compress point cloud data for automotive LiDAR sensors.

It presents a comprehensive taxonomy that categorizes these approaches into four main groups, comparing and discussing them across several important metrics.