Abstract

Time-gated non-line-of-sight (NLOS) imaging methods reconstruct scenes hidden around a corner by inverting the optical path of indirect photons measured at visible surfaces. These methods are, however, hindered by intricate, time-consuming calibration processes involving expensive capture hardware. Simulation of transient light transport in synthetic 3D scenes has become a powerful but computationally-intensive alternative for analysis and benchmarking of NLOS imaging methods. NLOS imaging methods also suffer from high computational complexity. In our work, we rely on dimensionality reduction to provide a real-time simulation framework for NLOS imaging performance analysis. We extend steady-state light transport in self-contained 2D worlds to take into account the propagation of time-resolved illumination by reformulating the transient path integral in 2D. We couple it with the recent phasor-field formulation of NLOS imaging to provide an end-to-end simulation and imaging pipeline that incorporates different NLOS imaging camera models. Our pipeline yields real-time NLOS images and progressive refinement of light transport simulations. We allow comprehensive control on a wide set of scene, rendering, and NLOS imaging parameters, providing effective real-time analysis of their impact on reconstruction quality. We illustrate the effectiveness of our pipeline by validating 2D counterparts of existing 3D NLOS imaging experiments, and provide an extensive analysis of imaging performance including a wider set of NLOS imaging conditions, such as filtering, reflectance, and geometric features in NLOS imaging setups.

Paper

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Bibtex

@article{pena2025flatland, author={Pe\~{n}a, Mar\'{i}a and Gutierrez, Diego and Marco, Julio}, journal={IEEE Transactions on Computational Imaging}, title={Looking Around Flatland: End-to-End 2D Real-Time NLOS Imaging}, year={2025}, volume={11}, number={}, pages={189-200}, keywords={Imaging;Nonlinear optics;Transient analysis;Three-dimensional displays;Rendering (computer graphics);Relays;Image reconstruction;Real-time systems;Sensors;Cameras;Transient rendering;NLOS imaging;computational imaging}, doi={10.1109/TCI.2025.3536092} }

Acknowledgments

This work was supported by the European Union's European Defense Fund Program through the ENLIGHTEN project under grant agreement No. 101103242. We would like to thank Diego Royo for his help generating the 2D exhaustive capture and Daniel Subias for his help with figures.