FOG-Zip: Bitstream Compression for Octree-Encoded LiDAR Data

• Author(s): Roriz, Ricardo João Rei ; Cabral, Jorge ; Pinto, Sandro ; Gomes, Tiago Manuel Ribeiro
• Date: 2025
• Persistent ID: https://hdl.handle.net/1822/97805
• Origin: RepositóriUM - Universidade do Minho
• Document Type: Journal article
• Language: English
• Contributor(s): Universidade do Minho

Description

Light detection and ranging (LiDAR) sensors play a critical role in enabling precise and reliable environmental perception for autonomous vehicles. However, handling the large amounts of data they generate presents a significant challenge. With the emergence of standards, such as the geometry based point cloud compression (G-PCC) standard, octrees have been used as a key data structure for compressing 3-D light detection and ranging (LiDAR) data. Despite their advantages, octrees often lead to high memory utilization and computational overhead, particularly when dealing with high-resolution datasets, limiting their utilization in systems with real-time requirements. This letter presents FOG-zip: a hardware-accelerated octree compression approach designed for embedded systems with limited resources. Experimental results demonstrate that FOG-zip achieves up to a 27.8% reduction in data size compared to the same uncompressed octree bitstream, while processing each frame within the frame rate limits of the sensor used.