Non-line-of-sight imaging in the presence of scattering media using phasor fields.

Non-line-of-sight (NLOS) imaging aims to reconstruct partially or completely occluded scenes. Recent approaches have demonstrated high-quality reconstructions of complex scenes with arbitrary reflectance, occlusions, and significant multi-path effects. However, previous works focused on surface scattering only, which reduces the generality in more challenging scenarios such as scenes submerged in scattering media. In this work, we investigate current state-of-the-art NLOS imaging methods based on phasor fields to reconstruct scenes submerged in scattering media. We empirically analyze the capability of phasor fields in reconstructing complex synthetic scenes submerged in thick scattering media. We also apply the method to real scenes, showing that it performs similarly to recent diffuse optical tomography methods.

Non-line-of-sight imaging using phasor-field virtual wave optics.

Non-line-of-sight imaging allows objects to be observed when partially or fully occluded from direct view, by analysing indirect diffuse reflections off a secondary relay surface. Despite many potential applications1-9, existing methods lack practical usability because of limitations including the assumption of single scattering only, ideal diffuse reflectance and lack of occlusions within the hidden scene. By contrast, line-of-sight imaging systems do not impose any assumptions about the imaged scene, despite relying on the mathematically simple processes of linear diffractive wave propagation. Here we show that the problem of non-line-of-sight imaging can also be formulated as one of diffractive wave propagation, by introducing a virtual wave field that we term the phasor field. Non-line-of-sight scenes can be imaged from raw time-of-flight data by applying the mathematical operators that model wave propagation in a conventional line-of-sight imaging system. Our method yields a new class of imaging algorithms that mimic the capabilities of line-of-sight cameras. To demonstrate our technique, we derive three imaging algorithms, modelled after three different line-of-sight systems. These algorithms rely on solving a wave diffraction integral, namely the Rayleigh-Sommerfeld diffraction integral. Fast solutions to Rayleigh-Sommerfeld diffraction and its approximations are readily available, benefiting our method. We demonstrate non-line-of-sight imaging of complex scenes with strong multiple scattering and ambient light, arbitrary materials, large depth range and occlusions. Our method handles these challenging cases without explicitly inverting a light-transport model. We believe that our approach will help to unlock the potential of non-line-of-sight imaging and promote the development of relevant applications not restricted to laboratory conditions.

Adaptive polarization-difference transient imaging for depth estimation in scattering media.

Introducing polarization into transient imaging improves depth estimation in participating media, by discriminating reflective from scattered light transport and calculating depth from the former component only. Previous works have leveraged this approach under the assumption of uniform polarization properties. However, the orientation and intensity of polarization inside scattering media is nonuniform, both in the spatial and temporal domains. As a result of this simplifying assumption, the accuracy of the estimated depth worsens significantly as the optical thickness of the medium increases. In this Letter, we introduce a novel adaptive polarization-difference method for transient imaging, taking into account the nonuniform nature of polarization in scattering media. Our results demonstrate a superior performance for impulse-based transient imaging over previous unpolarized or uniform approaches.

Fast back-projection for non-line of sight reconstruction.

Recent works have demonstrated non-line of sight (NLOS) reconstruction by using the time-resolved signal from multiply scattered light. These works combine ultrafast imaging systems with computation, which back-projects the recorded space-time signal to build a probabilistic map of the hidden geometry. Unfortunately, this computation is slow, becoming a bottleneck as the imaging technology improves. In this work, we propose a new back-projection technique for NLOS reconstruction, which is up to a thousand times faster than previous work, with almost no quality loss. We base on the observation that the hidden geometry probability map can be built as the intersection of the three-bounce space-time manifolds defined by the light illuminating the hidden geometry and the visible point receiving the scattered light from such hidden geometry. This allows us to pose the reconstruction of the hidden geometry as the voxelization of these space-time manifolds, which has lower theoretic complexity and is easily implementable in the GPU. We demonstrate the efficiency and quality of our technique compared against previous methods in both captured and synthetic data.

Effects of Approximate Filtering on the Appearance of Bidirectional Texture Functions.

The BTF data structure was a breakthrough for appearance modeling in computer graphics. More research is needed though to make BTFs practical in rendering applications. We present the first systematic study of the effects of Approximate filtering on the appearance of BTFs, by exploring the spatial, angular and temporal domains over a varied set of stimuli. We perform our initial experiments on simple geometry and lighting, and verify our observations on more complex settings. We consider multi-dimensional filtering versus conventional mipmapping, and find that multi-dimensional filtering produces superior results. We examine the tradeoff between under- and oversampling, and find that different filtering strategies can be applied in each domain, while maintaining visual equivalence with respect to a ground truth. For example, we find that preserving contrast is more important in static than dynamic images, indicating greater levels of spatial filtering are possible for animations. We find that filtering can be performed more aggressively in the angular domain than in the spatial. Additionally, we find that high-level visual descriptors of the BTF are linked to the perceptual performance of pre-filtered approximations. In turn, some of these high-level descriptors correlate with low level statistics of the BTF. We show six different practical applications of applying our findings to improving filtering, rendering and compression strategies.