The Experts below are selected from a list of 285 Experts worldwide ranked by ideXlab platform
Ramesh Raskar - One of the best experts on this subject based on the ideXlab platform.
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Time-of-Flight Microwave Camera
Scientific Reports, 2015Co-Authors: Gregory Charvat, Andrew Temme, Micha Feigin, Ramesh RaskarAbstract:Microwaves can penetrate many obstructions that are opaque at visible wavelengths, however microwave imaging is challenging due to resolution limits associated with relatively small apertures and unrecoverable “stealth” regions due to the specularity of most objects at microwave frequencies. We demonstrate a multispectral Time-of-Flight microwave imaging system which overcomes these challenges with a large passive aperture to improve lateral resolution, multiple illumination points with a data fusion method to reduce stealth regions, and a frequency modulated continuous wave (FMCW) receiver to achieve depth resolution. The camera captures images with a resolution of 1.5 degrees, multispectral images across the X frequency band (8 GHz–12 GHz), and a time resolution of 200 ps (6 cm optical path in free space). Images are taken of objects in free space as well as behind drywall and plywood. This architecture allows “camera-like” behavior from a microwave imaging system and is practical for imaging everyday objects in the microwave spectrum.
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coded time of flight cameras sparse deconvolution to address multipath interference and recover time profiles
International Conference on Computer Graphics and Interactive Techniques, 2013Co-Authors: Achuta Kadambi, Refael Whyte, Ayush Bhandari, Lee Streeter, Christopher Barsi, Adrian A Dorrington, Ramesh RaskarAbstract: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.
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Picosecond Camera for Time-of-Flight Imaging
Imaging and Applied Optics, 2011Co-Authors: Andreas Velten, Moungi G Bawendi, Ramesh RaskarAbstract:We present an ultra-fast imaging system capable of capturing images with picosecond time resolution or movies with a frame rate of 5·10^11 frames per second. We demonstrate the use of this system to analyze subsurface scattering and multibounce light transport. We present an analysis of scattering in different materials and review some of the applications of multibounce light transport.
Radu Horaud - One of the best experts on this subject based on the ideXlab platform.
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Time-of-Flight Cameras
SpringerBriefs in Computer Science, 2020Co-Authors: Miles Hansard, Ouk Choi, Radu HoraudAbstract:International audienceThis book describes a variety of recent research into Time-of-Flight imaging. Time-of-Flight cameras are used to estimate 3D scene-structure directly, in a way that complements traditional multiple-view reconstruction methods. The first two chapters of the book explain the underlying measurement principle, and examine the associated sources of error and ambiguity. Chapters three and four are concerned with the geometric calibration of Time-of-Flight cameras, particularly when used in combination with ordinary colour cameras. The final chapter shows how to use Time-of-Flight data in conjunction with traditional stereo matching techniques. The five chapters, together, describe a complete depth and colour 3D reconstruction pipeline. This book will be useful to new researchers in the field of depth imaging, as well as to those who are working on systems that combine colour and Time-of-Flight cameras
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An overview of depth cameras and range scanners based on Time-of-Flight technologies
Machine Vision and Applications, 2016Co-Authors: Radu Horaud, Georgios Evangelidis, Miles Hansard, Clément MénierAbstract:Time-of-Flight (TOF) cameras are sensors that can measure the depths of scene-points, by illuminating the scene with a controlled laser or LED source, and then analyzing the reflected light. In this paper we will first describe the underlying measurement principles of Time-of-Flight cameras, including: (i) pulsed-light cameras, which measure directly the time taken for a light pulse to travel from the device to the object and back again, and (ii) continuous-wave modulated-light cameras, which measure the phase difference between the emitted and received signals, and hence obtain the travel time indirectly. We review the main existing designs, including prototypes as well as commercially available devices. We also review the relevant camera calibration principles, and how they are applied to TOF devices. Finally, we discuss the benefits and challenges of combined TOF and color camera systems. Keywords LIDAR · range scanners · single photon avalanche diode · Time-of-Flight cameras · 3D computer vision · active-light sensors
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Characterization of Time-of-Flight Data
Time-of-Flight Cameras, 2012Co-Authors: Miles Hansard, Ouk Choi, Radu HoraudAbstract:This chapter introduces the principles and difficulties of Time-of-Flight depth measurement. The depth images that are produced by Time-of-Flight cameras suffer from characteristic problems, which are divided into the following two classes. First, there are systematic errors, such as noise and ambiguity, which are directly related to the sensor. Second, there are nonsystematic errors, such as scattering and motion blur, which are more strongly related to the scene content. It is shown that these errors are often quite different from those observed in ordinary color images. The case of motion blur, which is particularly problematic, is examined in detail. A practical methodology for investigating the performance of depth cameras is presented. Time-of-Flight devices are compared to structured-light systems, and the problems posed by specular and translucent materials are investigated.
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Disambiguation of Time-of-Flight Data
Time-of-Flight Cameras, 2012Co-Authors: Miles Hansard, Ouk Choi, Radu HoraudAbstract:The maximum range of a Time-of-Flight camera is limited by the periodicity of the measured signal. Beyond a certain range, which is determined by the signal frequency, the measurements are confounded by phase wrapping. This effect is demonstrated in real examples. Several phase-unwrapping methods, which can be used to extend the range of Time-of-Flight cameras, are discussed. Simple methods can be based on the measured amplitude of the reflected signal, which is itself related to the depth of objects in the scene. More sophisticated unwrapping methods are based on zero-curl constraints, which enforce spatial consistency on the phase measurements. Alternatively, if more than one depth camera is used, then the data can be unwrapped by enforcing consistency among different views of the same scene point. The relative merits and shortcomings of these methods are evaluated, and the prospects for hardware-based approaches, involving frequency modulation are discussed.
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Calibration of Time-of-Flight Cameras
Time-of-Flight Cameras, 2012Co-Authors: Miles Hansard, Ouk Choi, Radu HoraudAbstract:This chapter describes the metric calibration of a Time-of-Flight camera including the internal parameters, and lens distortion. Once the camera has been calibrated, the 2D depth image can be transformed into a range map, which encodes the distance to the scene along each optical ray. It is convenient to use established calibration methods, which are based on images of a chequerboard pattern. The low resolution of the amplitude image, however, makes it difficult to detect the board reliably. Heuristic detection methods, based on connected image components, perform very poorly on this data. An alternative, geometrically principled method is introduced here, based on the Hough transform. The Hough method is compared to the standard OpenCV board-detection routine, by application to several hundred Time-of-Flight images. It is shown that the new method detects significantly more calibration boards, over a greater variety of poses, without any significant loss of accuracy.
Marvin L. Vestal - One of the best experts on this subject based on the ideXlab platform.
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Modern MALDI Time-of-Flight mass spectrometry
Journal of Mass Spectrometry, 2009Co-Authors: Marvin L. VestalAbstract:This paper focuses on development of Time-of-Flight (TOF) mass spectrometry in response to the invention of matrix-assisted laser desorption/ionization (MALDI). Before this breakthrough ionization technique for nonvolatile molecules, TOF was generally considered as a useful tool for exotic studies of ion properties but was not widely applied to analytical problems. Improved TOF instruments and software that allow the full potential power of MALDI to be applied to difficult biological applications are described. A theoretical approach to the design and optimization of MALDI-TOF instruments for particular applications is presented. Experimental data are provided that are in excellent agreement with theoretical predictions of resolving power and mass accuracy. Data on sensitivity and dynamic range using kilohertz laser rates are also summarized. These results indicate that combinations of high-performance MALDI-TOF and TOF-TOF with off-line high-capacity separations may ultimately provide throughput and dynamic range several orders of magnitude greater than those currently available with electrospray LC-MS and MS-MS.
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Time-of-Flight Mass Spectrometry
Selected Topics in Mass Spectrometry in the Biomolecular Sciences, 1997Co-Authors: Marvin L. VestalAbstract:The emphasis in this discussion is on Time-of-Flight mass spectrometry as it relates to present and potential biological applications. It is not intended to be a comprehensive review of Time-of-Flight technology. Some excellent reviews have been published recently, and the reader is referred to those for subjects not covered here. [1–3] We begin with a brief history covering some of the seminal developments, proceed to an overview of TOF theory and practice, and then discuss the present state-of-the-art of TOF instruments for biological applications. The discussion concludes with a brief (and perhaps cloudy) gaze into the future.
Ralf Zimmermann - One of the best experts on this subject based on the ideXlab platform.
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single photon ionization time of flight mass spectrometry with a pulsed electron beam pumped excimer vuv lamp for on line gas analysis setup and first results on cigarette smoke and human breath
Analytical Chemistry, 2005Co-Authors: F Muhlberger, Thorsten Streibel, J Wieser, And A Ulrich, Ralf ZimmermannAbstract:Single-photon ionization (SPI) using vacuum ultraviolet (VUV) light produced by an electron beam pumped rare gas excimer source has been coupled to a compact and mobile Time-of-Flight mass spectrometer (TOFMS). The novel device enables real-time on-line monitoring of organic trace substances in complex gaseous matrixes down to the ppb range. The pulsed VUV radiation of the light source is employed for SPI in the ion source of the TOFMS. Ion extraction is also carried out in a pulsed mode with a short time delay with respect to ionization. The experimental setup of the interface VUV light source/Time-of-Flight mass spectrometer is described, and the novel SPI-TOFMS system is characterized by means of standard calibration gases. Limits of detection down to 50 ppb for aliphatic and aromatic hydrocarbons were achieved. First on-line applications comprised real-time measurements of aromatic and aliphatic trace compounds in mainstream cigarette smoke, which represents a highly dynamic fluctuating gaseous matrix...
Miles Hansard - One of the best experts on this subject based on the ideXlab platform.
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Time-of-Flight Cameras
SpringerBriefs in Computer Science, 2020Co-Authors: Miles Hansard, Ouk Choi, Radu HoraudAbstract:International audienceThis book describes a variety of recent research into Time-of-Flight imaging. Time-of-Flight cameras are used to estimate 3D scene-structure directly, in a way that complements traditional multiple-view reconstruction methods. The first two chapters of the book explain the underlying measurement principle, and examine the associated sources of error and ambiguity. Chapters three and four are concerned with the geometric calibration of Time-of-Flight cameras, particularly when used in combination with ordinary colour cameras. The final chapter shows how to use Time-of-Flight data in conjunction with traditional stereo matching techniques. The five chapters, together, describe a complete depth and colour 3D reconstruction pipeline. This book will be useful to new researchers in the field of depth imaging, as well as to those who are working on systems that combine colour and Time-of-Flight cameras
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An overview of depth cameras and range scanners based on Time-of-Flight technologies
Machine Vision and Applications, 2016Co-Authors: Radu Horaud, Georgios Evangelidis, Miles Hansard, Clément MénierAbstract:Time-of-Flight (TOF) cameras are sensors that can measure the depths of scene-points, by illuminating the scene with a controlled laser or LED source, and then analyzing the reflected light. In this paper we will first describe the underlying measurement principles of Time-of-Flight cameras, including: (i) pulsed-light cameras, which measure directly the time taken for a light pulse to travel from the device to the object and back again, and (ii) continuous-wave modulated-light cameras, which measure the phase difference between the emitted and received signals, and hence obtain the travel time indirectly. We review the main existing designs, including prototypes as well as commercially available devices. We also review the relevant camera calibration principles, and how they are applied to TOF devices. Finally, we discuss the benefits and challenges of combined TOF and color camera systems. Keywords LIDAR · range scanners · single photon avalanche diode · Time-of-Flight cameras · 3D computer vision · active-light sensors
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Characterization of Time-of-Flight Data
Time-of-Flight Cameras, 2012Co-Authors: Miles Hansard, Ouk Choi, Radu HoraudAbstract:This chapter introduces the principles and difficulties of Time-of-Flight depth measurement. The depth images that are produced by Time-of-Flight cameras suffer from characteristic problems, which are divided into the following two classes. First, there are systematic errors, such as noise and ambiguity, which are directly related to the sensor. Second, there are nonsystematic errors, such as scattering and motion blur, which are more strongly related to the scene content. It is shown that these errors are often quite different from those observed in ordinary color images. The case of motion blur, which is particularly problematic, is examined in detail. A practical methodology for investigating the performance of depth cameras is presented. Time-of-Flight devices are compared to structured-light systems, and the problems posed by specular and translucent materials are investigated.
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Disambiguation of Time-of-Flight Data
Time-of-Flight Cameras, 2012Co-Authors: Miles Hansard, Ouk Choi, Radu HoraudAbstract:The maximum range of a Time-of-Flight camera is limited by the periodicity of the measured signal. Beyond a certain range, which is determined by the signal frequency, the measurements are confounded by phase wrapping. This effect is demonstrated in real examples. Several phase-unwrapping methods, which can be used to extend the range of Time-of-Flight cameras, are discussed. Simple methods can be based on the measured amplitude of the reflected signal, which is itself related to the depth of objects in the scene. More sophisticated unwrapping methods are based on zero-curl constraints, which enforce spatial consistency on the phase measurements. Alternatively, if more than one depth camera is used, then the data can be unwrapped by enforcing consistency among different views of the same scene point. The relative merits and shortcomings of these methods are evaluated, and the prospects for hardware-based approaches, involving frequency modulation are discussed.
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Calibration of Time-of-Flight Cameras
Time-of-Flight Cameras, 2012Co-Authors: Miles Hansard, Ouk Choi, Radu HoraudAbstract:This chapter describes the metric calibration of a Time-of-Flight camera including the internal parameters, and lens distortion. Once the camera has been calibrated, the 2D depth image can be transformed into a range map, which encodes the distance to the scene along each optical ray. It is convenient to use established calibration methods, which are based on images of a chequerboard pattern. The low resolution of the amplitude image, however, makes it difficult to detect the board reliably. Heuristic detection methods, based on connected image components, perform very poorly on this data. An alternative, geometrically principled method is introduced here, based on the Hough transform. The Hough method is compared to the standard OpenCV board-detection routine, by application to several hundred Time-of-Flight images. It is shown that the new method detects significantly more calibration boards, over a greater variety of poses, without any significant loss of accuracy.
