Indirect Time-of-Flight (iToF) cameras are a promising depth sensing technology. However, they are prone to errors caused by multi-path interference (MPI) and low signal-to-noise ratio (SNR). Traditional methods, after denoising, mitigate MPI by estimating a transient image that encodes depths. Recently, data-driven methods that jointly denoise and mitigate MPI have become state-of-the-art without using the intermediate transient representation. In this paper, we propose to revisit the transient representation. Using data-driven priors, we interpolate/extrapolate iToF frequencies and use them to estimate the transient image. Given direct ToF (dToF) sensors capture transient images, we name our method iToF2dToF. The transient representation is flexible. It can be integrated with different rule-based depth sensing algorithms that are robust to low SNR and can deal with ambiguous scenarios that arise in practice (e.g., specular MPI, optical cross-talk). We demonstrate the benefits of iToF2dToF over previous methods in real depth sensing scenarios.
Wyant College of Optical Sciences - University of Arizona（亚利桑那大学怀恩特光学科学学院）
This book chapter describes how spectral correlations in scattered light fields can be utilized for high-precision time-of-flight sensing. The chapter should serve as a gentle introduction and is intended for computational imaging scientists and students new to the fascinating topic of synthetic wavelength imaging. Technical details (such as detector or light source specifications) will be largely omitted. Instead, the similarities between different methods will be emphasized to "draw the bigger picture."
A variety of techniques such as light field, structured illumination, and time-of-flight (TOF) are commonly used for depth acquisition in consumer imaging, robotics and many other applications. Unfortunately, each technique suffers from its individual limitations preventing robust depth sensing. In this paper, we explore the strengths and weaknesses of combining light field and time-of-flight imaging, particularly the feasibility of an on-chip implementation as a single hybrid depth sensor. We refer to this combination as depth field imaging. Depth fields combine light field advantages such as…
University of Bonn（波恩大学）；Stanford University（斯坦福大学）
Computational photography encompasses a diversity of imaging techniques, but one of the core operations performed by many of them is to compute image differences. An intuitive approach to computing such differences is to capture several images sequentially and then process them jointly. Usually, this approach leads to artifacts when recording dynamic scenes. In this paper, we introduce a snapshot difference imaging approach that is directly implemented in the sensor hardware of emerging time-of-flight cameras. With a variety of examples, we demonstrate that the proposed snapshot difference ima…
Accurate Pose Estimation for Flight Platforms based on Divergent Multi-Aperture Imaging System
College of Aerospace Science and Engineering, National University of Defense Technology（国防科技大学航天科学与工程学院）；Institute of Intelligent Optical Measurement and Detection, Shenzhen University（深圳大学智能光学测量与检测研究院）
Time-of-flight (ToF) sensors provide an imaging modality fueling diverse applications, including LiDAR in autonomous driving, robotics, and augmented reality. Conventional ToF imaging methods estimate the depth by sending pulses of light into a scene and measuring the ToF of the first-arriving photons directly reflected from a scene surface without any temporal delay. As such, all photons following this first response are typically considered as unwanted noise. In this paper, we depart from the principle of using first-arriving photons and propose an all-photon ToF imaging method by incorporat…
Princeton University（普林斯顿大学）；King Abdullah University of Science and Technology（阿卜杜拉国王科技大学）
We introduce Mask-ToF, a method to reduce flying pixels (FP) in time-of-flight (ToF) depth captures. FPs are pervasive artifacts which occur around depth edges, where light paths from both an object and its background are integrated over the aperture. This light mixes at a sensor pixel to produce erroneous depth estimates, which can adversely affect downstream 3D vision tasks. Mask-ToF starts at the source of these FPs, learning a microlens-level occlusion mask which effectively creates a custom-shaped sub-aperture for each sensor pixel. This modulates the selection of foreground and backgroun…
We introduce an interferometric technique for passive time-of-flight imaging and depth sensing at micrometer axial resolutions. Our technique uses a full-field Michelson interferometer, modified to use sunlight as the only light source. The large spectral bandwidth of sunlight makes it possible to acquire micrometer-resolution time-resolved scene responses, through a simple axial scanning operation. Additionally, the angular bandwidth of sunlight makes it possible to capture time-of-flight measurements insensitive to indirect illumination effects, such as interreflections and subsurface scatte…
Massachusetts Institute of Technology（麻省理工学院）；University of Waikato（怀卡托大学）
Time-of-flight (ToF) cameras calculate depth maps by reconstructing phase shifts of amplitude-modulated signals. For broad illumination or 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.
To conduct a radiomics or deep learning research experiment, the radiologists or physicians need to grasp the needed programming skills, which, however, could be frustrating and costly when they have limited coding experience. In this paper, we present DARWIN, a flexible research platform with a graphical user interface for medical imaging research. Our platform is consists of a radiomics module and a deep learning module. The radiomics module can extract more than 1000 dimension features(first-, second-, and higher-order) and provided many draggable supervised and unsupervised machine learnin…
A comprehensive study of time-of-flight non-line-of-sight imaging
Universidad de Zaragoza–I3A（萨拉戈萨大学–I3A）；University of Wisconsin–Madison（威斯康星大学麦迪逊分校）；Department of Data Science, Inha University（数据科学系，inha大学）；Politecnico di Milano（米兰理工学院）
Depth cameras are emerging as a cornerstone modality with diverse applications that directly or indirectly rely on measured depth, including personal devices, robotics, and self-driving vehicles. Although time-of-flight (ToF) methods have fueled these applications, the precision and robustness of ToF methods is limited by relying on photon time-tagging or modulation after photo-conversion. Successful optical modulation approaches have been restricted fiber-coupled modulation with large coupling losses or interferometric modulation with sub-cm range, and the precision gap between interferometri…
Time of flight based Non-line-of-sight (NLOS) imaging approaches require precise calibration of illumination and detector positions on the visible scene to produce reasonable results. If this calibration error is sufficiently high, reconstruction can fail entirely without any indication to the user. In this work, we highlight the necessity of building autocalibration into NLOS reconstruction in order to handle mis-calibration. We propose a forward model of NLOS measurements that is differentiable with respect to both, the hidden scene albedo, and virtual illumination and detector positions. Wi…
Sony Corporation（索尼公司）；Rice University（莱斯大学）；Indian Institute of Technology Madras（印度理工学院马德拉斯分校）
Transient imaging or light-in-flight techniques capture the propagation of an ultra-short pulse of light through a scene, which in effect captures the optical impulse response of the scene. Recently, it has been shown that we can capture transient images using commercially available Time-of-Flight (ToF) systems such as Photonic Mixer Devices (PMD). In this paper, we propose `spatial phase-sweep', a technique that exploits the speed of light to increase the temporal resolution beyond the 100 picosecond limit imposed by current electronics. Spatial phase-sweep uses a linear array of light source…
Multi-view imaging systems enable uniform coverage of 3D space and reduce the impact of occlusion, which is beneficial for 3D object detection and tracking accuracy. However, existing imaging systems built with multi-view cameras or depth sensors are limited by the small applicable scene and complicated composition. In this paper, we propose a wireless multi-view multi-modal 3D imaging system generally applicable to large outdoor scenes, which consists of a master node and several slave nodes. Multiple spatially distributed slave nodes equipped with cameras and LiDARs are connected to form a w…
Single-Photon Avalanche Diodes (SPAD) are affordable photodetectors, capable to collect extremely fast low-energy events, due to their single-photon sensibility. This makes them very suitable for time-of-flight-based range imaging systems, allowing to reduce costs and power requirements, without sacrifizing much temporal resolution. In this work we describe a computational model to simulate the behaviour of SPAD sensors, aiming to provide a realistic camera model for time-resolved light transport simulation, with applications on prototyping new reconstructions techniques based on SPAD time-of-…
Microsoft AIT - Advanced Imaging Technologies（微软高级成像技术部）；CMU（卡内基梅隆大学）；Microsoft Research - Cambridge（微软剑桥研究院）
We propose a computational model for shape, illumination and albedo inference in a pulsed time-of-flight (TOF) camera. In contrast to TOF cameras based on phase modulation, our camera enables general exposure profiles. This results in added flexibility and requires novel computational approaches. To address this challenge we propose a generative probabilistic model that accurately relates latent imaging conditions to observed camera responses. While principled, realtime inference in the model turns out to be infeasible, and we propose to employ efficient non-parametric regression trees to appr…
Technical University of Munich（慕尼黑工业大学）；Huawei Noah’s Ark Lab（华为诺亚方舟实验室）
Indirect Time-of-Flight (I-ToF) imaging is a widespread way of depth estimation for mobile devices due to its small size and affordable price. Previous works have mainly focused on quality improvement for I-ToF imaging especially curing the effect of Multi Path Interference (MPI). These investigations are typically done in specifically constrained scenarios at close distance, indoors and under little ambient light. Surprisingly little work has investigated I-ToF quality improvement in real-life scenarios where strong ambient light and far distances pose difficulties due to an extreme amount of…
