FOG-Zip: Bitstream Compression for Octree-Encoded LiDAR Data
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 G-PCC standard, octrees have been used as a key data structure for compressing 3D 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 hardwareaccelerated 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.
Authors
- Jorge Cabral (ORCID: https://orcid.org/0000-0001-9954-9746)
- Sandro Pinto (ORCID: https://orcid.org/0000-0003-4580-7484)
- Tiago Gomes (ORCID: https://orcid.org/0000-0002-4071-9015)
- Ricardo Roriz (ORCID: https://orcid.org/0000-0002-8543-550X)
Institutions
- University of Minho (PT)
Publication Details
- Journal
- IEEE Sensors Letters
- Published
- 2025-07-14
- DOI
- https://doi.org/10.1109/lsens.2025.3588338
- Primary Topic
- Advanced Vision and Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00