All-photon Polarimetric Time-of-Flight Imaging (CVPR 2022)

Time-of-flight (ToF) sensors provide an image modality fueling applications across domains, including lidar in autonomous driving, robotics, and augmented reality. Conventional ToF imaging methods estimate the depth of a scene point by sending pulses of light into a scene and measuring the time of flight of the first arriving photons that are returned from the scene, the ones directly reflected from a scene surface without any temporal delay. As such, all photons following this first response are typically considered as unwanted noise, including multi-bounce and sub-surface scattering of real-world materials. While multi-bounce scene interreflections have been extensively in recent work on non-line-of-sight imaging, we investigate temporally resolved sub-surface scattering in this work. We depart from the principle of first arrival and instead propose an all-photon ToF imaging method relying on polarization changes that analyzes both first- and late-arriving photons for shape and material scene understanding. To this end, we propose a novel capture method, reflectance model, and a reconstruction algorithm that exploits the polarization state of light changes after reflection in addition to ToF information. The proposed temporal-polarimetric imaging method allows for accurate geometric and material information of the scene by utilizing all photons captured by the system, decoded by polarization cues, outperforming all tested existing methods in simulation and experimentally.

Seung-Hwan Baek, Felix Heide

The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2022

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