Introduction To Stochastic Calculus With Applications

Kinect range sensing

https://shura.shu.ac.uk/7180/1/Rodriggues_%2D_optical_techniques_%2D_Review_MIA_revision_v9.pdf

Optical techniques for 3D surface reconstruction in computer-assisted laparoscopic surgery.

With the introduction of the Microsoft Kinect for Windows v2 (Kinect v2), an exciting new sensor is available to robotics and computer vision researchers. Similar to the original Kinect, the sensor is capable of acquiring accurate depth images at high rates. This is useful for robot navigation as dense and robust maps of the environment can be created. Opposed to the original Kinect working with the structured light technology, the Kinect v2 is based on the time-of-flight measurement principle and might also be used outdoors in sunlight. In this paper, we evaluate the application of the Kinect v2 depth sensor for mobile robot navigation. The results of calibrating the intrinsic camera parameters are presented and the minimal range of the depth sensor is examined. We analyze the data quality of the measurements for indoors and outdoors in overcast and direct sunlight situations. To this end, we introduce empirically derived noise models for the Kinect v2 sensor in both axial and lateral directions. The noise models take the measurement distance, the angle of the observed surface, and the sunlight incidence angle into account. These models can be used in post-processing to filter the Kinect v2 depth images for a variety of applications.

/pdf/kinect-v2-for-mobile-robot-navigation-evaluation-and-4nmfts5p9t.pdf

Kinect v2 for mobile robot navigation: Evaluation and modeling

By using time-of-flight information encoded in multiply scattered light, it is possible to reconstruct images of objects hidden from the camera’s direct line of sight. Here, we present a non-line-of-sight imaging system that uses a single-pixel, single-photon avalanche diode (SPAD) to collect time-of-flight information. Compared to earlier systems, this modification provides significant improvements in terms of power requirements, form factor, cost, and reconstruction time, while maintaining a comparable time resolution. The potential for further size and cost reduction of this technology make this system a good base for developing a practical system that can be used in real world applications.

Non-line-of-sight imaging using a time-gated single photon avalanche diode.

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.

/pdf/coded-time-of-flight-cameras-sparse-deconvolution-to-address-4ekubzmjgt.pdf

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

Time-of-flight range cameras acquire a three-dimensional image of a scene simultaneously for all pixels from a single
viewing location. Attempts to use range cameras for metrology applications have been hampered by the multi-path
problem, which causes range distortions when stray light interferes with the range measurement in a given pixel.
Correcting multi-path distortions by post-processing the three-dimensional measurement data has been investigated, but
enjoys limited success because the interference is highly scene dependent. An alternative approach based on separating
the strongest and weaker sources of light returned to each pixel, prior to range decoding, is more successful, but has only
been demonstrated on custom built range cameras, and has not been suitable for general metrology applications. In this
paper we demonstrate an algorithm applied to both the Mesa Imaging SR-4000 and Canesta Inc. XZ-422 Demonstrator
unmodified off-the-shelf range cameras. Additional raw images are acquired and processed using an optimization
approach, rather than relying on the processing provided by the manufacturer, to determine the individual component
returns in each pixel. Substantial improvements in accuracy are observed, especially in the darker regions of the scene.

/pdf/separating-true-range-measurements-from-multi-path-and-4vke21na8h.pdf

Separating true range measurements from multi-path and scattering interference in commercial range cameras

Current Time-of-Flight approaches mainly incorporate an continuous wave intensity modulation approach. The phase reconstruction is performed using multiple phase images with different phase shifts which is equivalent to sampling the inherent correlation function at different locations. This active imaging approach delivers a very specific set of influences, on the signal processing side as well as on the optical side, which all have an effect on the resulting depth quality. Applying ToF information in real application therefore requires to tackle these effects in terms of specific calibration approaches. This survey gives an overview over the current state of the art in ToF sensor calibration.

https://ipm.iwr.uni-heidelberg.de/publications/PDFs/2013/Lefloch_ToF2013.pdf

Technical Foundation and Calibration Methods for Time-of-Flight Cameras

Amplitude-modulated continuous wave (AMCW) time-of-flight (ToF) range imaging cameras measure distance by illuminating the scene with amplitude-modulated light and measuring the phase difference between the transmitted and reflected modulation envelope. This method of optical range measurement suffers from errors caused by multiple propagation paths, motion, phase wrapping, and nonideal amplitude modulation. In this paper a ToF camera is modified to operate in modes analogous to continuous wave (CW) and stepped frequency continuous wave (SFCW) lidar. In CW operation the velocity of objects can be measured. CW measurement of velocity was linear with true velocity (R2=0.9969). Qualitative analysis of a complex scene confirms that range measured by SFCW is resilient to errors caused by multiple propagation paths, phase wrapping, and nonideal amplitude modulation which plague AMCW operation. In viewing a complicated scene through a translucent sheet, quantitative comparison of AMCW with SFCW demonstrated a reduction in the median error from -1.3  m to -0.06  m with interquartile range of error reduced from 4.0 m to 0.18 m.

/pdf/application-of-lidar-techniques-to-time-of-flight-range-2pwrjqh6iq.pdf

Application of lidar techniques to time-of-flight range imaging

Hadamard multiplexing provides a considerable SNR boost over additive random noise but Poisson noise such as photon noise reduces the boost. We develop the theory for full H-matrix Hadamard transform imaging under additive and Poisson noise effects. We show that H-matrix encoding results in no effect on average on the noise level due to Poisson noise sources while preferentially reducing additive noise. We use this result to explain the wavelength-dependent varying SNR boost in a Hadamard hyperspectral imager and argue that such a preferential boost is useful when the main noise source is indeterminant or varying.

/pdf/optical-full-hadamard-matrix-multiplexing-and-noise-effects-5y5sg1xzoj.pdf

Lee Streeter

Papers

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

Separating true range measurements from multi-path and scattering interference in commercial range cameras

Technical Foundation and Calibration Methods for Time-of-Flight Cameras

Application of lidar techniques to time-of-flight range imaging

Optical full Hadamard matrix multiplexing and noise effects.