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US 2024/0202948 A1Published application
Non-line-of-sight imaging via neural transient field
AssigneeShanghaitech University
InventorsSiyuan SHEN, Zi WANG, Shiying LI, Jingyi YU
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Abstract
A novel neural modeling framework Neural Transient Field (NeTF) is provided for non-line-of-sight (NLOS) imaging. NeTF recovers the 5D transient function in both spatial location and direction, and the training data input is parametrized on the spherical wave-fronts. A Markov chain Monte Carlo (MCMC) algorithm is used to account for sparse and unbalanced sampling in NeTF.
Claims18
A computer-implemented method for imaging a non-line-of-sight (NLOS) scene, comprising:
- encoding, by a computing system, a neural transient field onto a Multi-Layer Perception (MLP), wherein the neural transient field represents the NLOS scene as a continuous 5D function of transient;
- feeding a plurality of transient pixels captured by a time-resolved detector from a plurality of detection spots on a relay wall to the MLP;
- outputting a volume density and a surface reflectance along a direction by the MLP in accordance with the plurality of transient pixels;
- and
- reconstructing the NLOS scene in accordance with the volume density and the surface reflectance.
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