Achuta Kadambi

Active Printed Materials for Complex Self-Evolving Deformations

We propose a new design of complex self-evolving structures that vary over time due to environmental interaction. In conventional 3D printing systems, materials are meant to be stable rather than active and fabricated models are designed and printed as static objects. Here, we introduce a novel approach for simulating and fabricating self-evolving structures that transform into a predetermined shape, changing property and function after fabrication. The new locally coordinated bending primitives combine into a single system, allowing for a global deformation which can stretch, fold and bend given environmental stimulus.

Coded time of flight cameras: sparse deconvolution to address multipath interference and recover time profiles

Time of flight cameras produce real-time range maps at a relatively low cost using continuous wave amplitude modulation and demodulation. However, they are geared to measure range (or phase) for a single reflected bounce of light and suffer from systematic errors due to multipath interference. We re-purpose the conventional time of flight device for a new goal: to recover per-pixel sparse time profiles expressed as a sequence of impulses. With this modification, we show that we can not only address multipath interference but also enable new applications such as recovering depth of near-transparent surfaces, looking through diffusers and creating time-profile movies of sweeping light. Our key idea is to formulate the forward amplitude modulated light propagation as a convolution with custom codes, record samples by introducing a simple sequence of electronic time delays, and perform sparse deconvolution to recover sequences of Diracs that correspond to multipath returns. Applications to computer vision include ranging of near-transparent objects and subsurface imaging through diffusers. Our low cost prototype may lead to new insights regarding forward and inverse problems in light transport.

Resolving multipath interference in time-of-flight imaging via modulation frequency diversity and sparse regularization

Time-of-flight (ToF) cameras calculate depth maps by reconstructing phase shifts of amplitude-modulated signals. For broad illumination of transparent objects, reflections from multiple scene points can illuminate a given pixel, giving rise to an erroneous depth map. We report here a sparsity-regularized solution that separates K interfering components using multiple modulation frequency measurements. The method maps ToF imaging to the general framework of spectral estimation theory and has applications in improving depth profiles and exploiting multiple scattering.

Polarized 3D: High-Quality Depth Sensing with Polarization Cues

Coarse depth maps can be enhanced by using the shape information from polarization cues. We propose a framework to combine surface normals from polarization (hereafter polarization normals) with an aligned depth map. Polarization normals have not been used for depth enhancement before. This is because polarization normals suffer from physics-based artifacts, such as azimuthal ambiguity, refractive distortion and fronto-parallel signal degradation. We propose a framework to overcome these key challenges, allowing the benefits of polarization to be used to enhance depth maps. Our results demonstrate improvement with respect to state-of-the-art 3D reconstruction techniques.

Occluded Imaging with Time-of-Flight Sensors

We explore the question of whether phase-based time-of-flight (TOF) range cameras can be used for looking around corners and through scattering diffusers. By connecting TOF measurements with theory from array signal processing, we conclude that performance depends on two primary factors: camera modulation frequency and the width of the specular lobe (“shininess”) of the wall. For purely Lambertian walls, commodity TOF sensors achieve resolution on the order of meters between targets. For seemingly diffuse walls, such as posterboard, the resolution is drastically reduced, to the order of 10cm. In particular, we find that the relationship between reflectance and resolution is nonlinear—a slight amount of shininess can lead to a dramatic improvement in resolution. Since many realistic scenes exhibit a slight amount of shininess, we believe that off-the-shelf TOF cameras can look around corners.

A light transport model for mitigating multipath interference in Time-of-flight sensors

Continuous-wave Time-of-flight (TOF) range imaging has become a commercially viable technology with many applications in computer vision and graphics. However, the depth images obtained from TOF cameras contain scene dependent errors due to multipath interference (MPI). Specifically, MPI occurs when multiple optical reflections return to a single spatial location on the imaging sensor. Many prior approaches to rectifying MPI rely on sparsity in optical reflections, which is an extreme simplification. In this paper, we correct MPI by combining the standard measurements from a TOF camera with information from direct and global light transport. We report results on both simulated experiments and physical experiments (using the Kinect sensor). Our results, evaluated against ground truth, demonstrate a quantitative improvement in depth accuracy.

Demultiplexing illumination via low cost sensing and nanosecond coding

Several computer vision algorithms require a sequence of photographs taken in different illumination conditions, which has spurred development in the area of illumination multiplexing. Various techniques for optimizing the multiplexing process already exist, but are geared toward regular or high speed cameras. Such cameras are fast, but code on the order of milliseconds. In this paper we propose a fusion of two popular contexts, time of flight range cameras and illumination multiplexing. Time of flight cameras are a low cost, consumer-oriented technology capable of acquiring range maps at 30 frames per second. Such cameras have a natural connection to conventional illumination multiplexing strategies as both paradigms rely on the capture of multiple shots and synchronized illumination. While previous work on illumination multiplexing has exploited coding at millisecond intervals, we repurpose sensors that are ordinarily used in time of flight imaging to demultiplex via nanosecond coding strategies.

Sparse Linear Operator identification without sparse regularization? Applications to mixed pixel problem in Time-of-Flight/Range imaging

In this paper, we consider the problem of Sparse Linear Operator identification which is also linked with the topic of Sparse Deconvolution. In its abstract form, the problem can be stated as follows: Given a well behaved probing function, is it possible to identify a Sparse Linear Operator from its response to the function? We present a constructive solution to this problem. Furthermore, our approach is devoid of any sparsity inducing penalty term and explores the idea of parametric modeling. Consequently, our algorithm is non-iterative by design and circumvents tuning of any regularization parameter. Our approach is computationally efficient when compared the ℓ0/ℓ1-norm regularized counterparts. Our work addresses a problem of industrial significance: decomposition of mixed-pixels in Time-of-Flight/Range imaging. In this case, each pixel records range measurements from multiple contributing depths and the goal is to isolate each depth. Practical experiments corroborate our theoretical set-up and establish the efficiency of our approach, that is, speed-up in processing with lesser mean squared error. We also derive Cramér-Rao Bounds for performance characterization.

Association of early changes in 1H MRSI parameters with survival for patients with newly diagnosed glioblastoma receiving a multimodality treatment regimen.

Background The heterogeneous biology of glioblastoma (GBM) emphasizes the need for imaging methods to assess tumor burden and assist in evaluating individual patients. The purpose of this study was to investigate early changes in metrics from 3D 1H magnetic resonance spectroscopic imaging (MRSI) data, compare them with anatomic lesion volumes, and determine whether they were associated with survival for patients with newly diagnosed GBM receiving a multimodality treatment regimen. Methods Serial MRI and MRSI scans provided estimates of anatomic lesion volumes and levels of choline, creatine, N-acetylaspartate, lactate, and lipid. The association of metrics derived from these data with survival was assessed using Cox proportional hazards models with adjustments for age, Karnofsky performance score, and extent of resection. Temporal changes in parameters were evaluated using a Wilcoxon signed rank test. Results Anatomic lesion volumes at the post-radiotherapy (RT) scan, metabolic lesion volume at mid-RT and post-RT scans, as well as metrics describing levels of choline, lactate, and lipid were associated with overall survival. There was a significant reduction in the enhancing lesion volume, increase in T2 lesion volume from mid-RT to post-RT, and decrease in parameters describing metabolite levels during these early time points. Conclusion The MRSI data provided metrics that described the effects of treatment on the metabolic lesion burden and were associated with overall survival. This suggests that adding these parameters to standard assessments of changes in anatomic lesion volumes could contribute to making early decisions about the efficacy of such combination therapies.

Macroscopic Interferometry: Rethinking Depth Estimation with Frequency-Domain Time-of-Flight

A form of meter-scale, macroscopic interferometry is proposed using conventional time-of-flight (ToF) sensors. Today, ToF sensors use phase-based sampling, where the phase delay between emitted and received, high-frequency signals encodes distance. This paper examines an alternative ToF architecture, inspired by micron-scale, microscopic interferometry, that relies only on frequency sampling: we refer to our proposed macroscopic technique as Frequency-Domain Time of Flight (FD-ToF). The proposed architecture offers several benefits over existing phase ToF systems, such as robustness to phase wrapping and implicit resolution of multi-path interference, all while capturing the same number of subframes. A prototype camera is constructed to demonstrate macroscopic interferometry at meter scale.