Spatial Calibration of Diffuse LiDARs

2026-03-06

AI Summary

This work addresses the challenge of precise spatial alignment between diffuse direct time-of-flight (dToF) LiDAR and RGB images, which is hindered by the wide field of view that invalidates the conventional single-ray assumption. The authors propose a spatial calibration method that scans reflective patches and employs background subtraction to estimate, for each LiDAR pixel, its effective support region and relative spatial sensitivity on the RGB image plane. This approach yields the first spatial response map for dToF LiDAR pixels, overcoming the limitations of traditional cross-modal calibration that relies on the single-ray model. Experimental validation on the ams OSRAM TMF8828 sensor demonstrates that the method establishes high-precision cross-modal correspondences, significantly enhancing multimodal fusion quality.

Technology Category

• Computer Vision: Multi-modal Vision
• Intelligent Robots: Multimodal Perception & Sensor Fusion
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems

Application Category

• Search and Retrieval-Augmented AI: Retrieval-Augmented Generation (RAG) and multi-modal RAG
• Semantics and Knowledge: Methods to enhance, augment, integrate or synergize semantic models such as knowledge graphs and LLMs
• Systems and Infrastructure for Web, Mobile and WoT: Location- and context-aware Web and WoT applications and services

Abstract

Diffuse direct time-of-flight LiDARs report per-pixel depth histograms formed by aggregating photon returns over a wide instantaneous field of view, violating the single-ray assumption behind standard LiDAR-RGB calibration. We present a simple spatial calibration procedure that estimates, for each diffuse LiDAR pixel, its footprint (effective support region) and relative spatial sensitivity in a co-located RGB image plane. Using a scanned retroreflective patch with background subtraction, we recover per-pixel response maps that provide an explicit LiDAR-to-RGB correspondence for cross-modal alignment and fusion. We demonstrate the method on the ams OSRAM TMF8828.

Problem

• Diffuse LiDAR
• Spatial Calibration
• LiDAR-RGB Alignment
• Depth Histogram
• Cross-modal Fusion

Innovation

• diffuse LiDAR
• spatial calibration
• time-of-flight
• cross-modal alignment
• footprint estimation