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  1. We introduce Doppler time-of-flight (D-ToF) rendering, an extension of ToF rendering for dynamic scenes, with applications in simulating D-ToF cameras. D-ToF cameras use high-frequency modulation of illumination and exposure, and measure the Doppler frequency shift to compute the radial velocity of dynamic objects. The time-varying scene geometry and high-frequency modulation functions used in such cameras make it challenging to accurately and efficiently simulate their measurements with existing ToF rendering algorithms. We overcome these challenges in a twofold manner: To achieve accuracy, we derive path integral expressions for D-ToF measurements under global illumination and form unbiased Monte Carlo estimates of these integrals. To achieve efficiency, we develop a tailored time-path sampling technique that combines antithetic time sampling with correlated path sampling. We show experimentally that our sampling technique achieves up to two orders of magnitude lower variance compared to naive time-path sampling. We provide an open-source simulator that serves as a digital twin for D-ToF imaging systems, allowing imaging researchers, for the first time, to investigate the impact of modulation functions, material properties, and global illumination on D-ToF imaging performance.

     
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    Free, publicly-accessible full text available December 5, 2024
  2. Abstract

    Ultrasonically-sculpted gradient-index optical waveguides enable non-invasive light confinement inside scattering media. The confinement level strongly depends on ultrasound parameters (e.g., amplitude, frequency), and medium optical properties (e.g., extinction coefficient). We develop a physically-accurate simulator, and use it to quantify these dependencies for a radially-symmetric virtual optical waveguide. Our analysis provides insights for optimizing virtual optical waveguides for given applications. We leverage these insights to configure virtual optical waveguides that improve light confinement fourfold compared to previous configurations at five mean free paths. We show that virtual optical waveguides enhance light throughput by 50% compared to an ideal external lens, in a medium with bladder-like optical properties at one transport mean free path. We corroborate these simulation findings with real experiments: we demonstrate, for the first time, that virtual optical waveguides recycle scattered light, and enhance light throughput by 15% compared to an external lens at five transport mean free paths.

     
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    Free, publicly-accessible full text available December 1, 2024
  3. Abstract

    Let$$\textbf{p}$$pbe a configuration ofnpoints in$$\mathbb R^d$$Rdfor somenand some$$d \ge 2$$d2. Each pair of points defines an edge, which has a Euclidean length in the configuration. A path is an ordered sequence of the points, and a loop is a path that begins and ends at the same point. A path or loop, as a sequence of edges, also has a Euclidean length, which is simply the sum of its Euclidean edge lengths. We are interested in reconstructing$$\textbf{p}$$pgiven a set of edge, path and loop lengths. In particular, we consider the unlabeled setting where the lengths are given simply as a set of real numbers, and are not labeled with the combinatorial data describing which paths or loops gave rise to these lengths. In this paper, we study the question of when$$\textbf{p}$$pwill be uniquely determined (up to an unknowable Euclidean transform) from some given set of path or loop lengths through an exhaustive trilateration process. Such a process has already been used for the simpler problem of reconstruction using unlabeled edge lengths. This paper also provides a complete proof that this process must work in that edge-setting when given a sufficiently rich set of edge measurements and assuming that$$\textbf{p}$$pis generic.

     
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  4. Grid-free Monte Carlo methods such aswalk on spherescan be used to solve elliptic partial differential equations without mesh generation or global solves. However, such methods independently estimate the solution at every point, and hence do not take advantage of the high spatial regularity of solutions to elliptic problems. We propose a fast caching strategy which first estimates solution values and derivatives at randomly sampled points along the boundary of the domain (or a local region of interest). These cached values then provide cheap, output-sensitive evaluation of the solution (or its gradient) at interior points, via a boundary integral formulation. Unlike classic boundary integral methods, our caching scheme introduces zero statistical bias and does not require a dense global solve. Moreover we can handle imperfect geometry (e.g., with self-intersections) and detailed boundary/source terms without repairing or resampling the boundary representation. Overall, our scheme is similar in spirit tovirtual point lightmethods from photorealistic rendering: it suppresses the typical salt-and-pepper noise characteristic of independent Monte Carlo estimates, while still retaining the many advantages of Monte Carlo solvers: progressive evaluation, trivial parallelization, geometric robustness,etc.We validate our approach using test problems from visual and geometric computing.

     
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    Free, publicly-accessible full text available August 1, 2024
  5. Grid-free Monte Carlo methods based on thewalk on spheres (WoS)algorithm solve fundamental partial differential equations (PDEs) like the Poisson equation without discretizing the problem domain or approximating functions in a finite basis. Such methods hence avoid aliasing in the solution, and evade the many challenges of mesh generation. Yet for problems with complex geometry, practical grid-free methods have been largely limited to basic Dirichlet boundary conditions. We introduce thewalk on stars (WoSt)algorithm, which solves linear elliptic PDEs with arbitrary mixed Neumann and Dirichlet boundary conditions. The key insight is that one can efficiently simulate reflecting Brownian motion (which models Neumann conditions) by replacing the balls used by WoS withstar-shapeddomains. We identify such domains via the closest point on the visibility silhouette, by simply augmenting a standard bounding volume hierarchy with normal information. Overall, WoSt is an easy modification of WoS, and retains the many attractive features of grid-free Monte Carlo methods such as progressive and view-dependent evaluation, trivial parallelization, and sublinear scaling to increasing geometric detail.

     
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    Free, publicly-accessible full text available August 1, 2024
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