LiDARSpectra: Synthetic Indoor Spectral Mapping with Low-cost LiDARs

We introduce LiDARSpectra, a novel approach utilizing mobile-integrated commodity Light Detection and Ranging (LiDAR) signals for synthetic indoor light spectral mapping. Our method incorporates an innovative material estimation algorithm into the LiDAR signal processing pipeline, accurately simulating reflected wavelengths from indoor surfaces. Utilizing low-resolution LiDAR scans enriched with material information, it eliminates the need for deploying dedicated spectral sensors, greatly simplifying the spectral mapping process. We validate our synthetic spectral maps against real sensor data and demonstrate their utility in applications such as indoor localization and solar energy provisioning. This presents an efficient solution for indoor spectral mapping with wide-ranging potential across fields like lighting design, indoor planting, environmental monitoring, and location-based services.