KinectFusion enables a user holding and moving a standard Kinect camera to rapidly create detailed 3D reconstructions of an indoor scene. Only the depth data from Kinect is used to track the 3D pose of the sensor and reconstruct, geometrically precise, 3D models of the physical scene in real-time. The capabilities of KinectFusion, as well as the novel GPU-based pipeline are described in full. Uses of the core system for low-cost handheld scanning, and geometry-aware augmented reality and physics-based interactions are shown. Novel extensions to the core GPU pipeline demonstrate object segmentation and user interaction directly in front of the sensor, without degrading camera tracking or reconstruction. These extensions are used to enable real-time multi-touch interactions anywhere, allowing any planar or non-planar reconstructed physical surface to be appropriated for touch.

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KinectFusion: real-time 3D reconstruction and interaction using a moving depth camera

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Principles Of Optics Electromagnetic Theory Of Propagation Interference And Diffraction Of Light

Consumer-grade range cameras such as the Kinect sensor have the potential to be used in mapping applications where accuracy requirements are less strict. To realize this potential insight into the geometric quality of the data acquired by the sensor is essential. In this paper we discuss the calibration of the Kinect sensor, and provide an analysis of the accuracy and resolution of its depth data. Based on a mathematical model of depth measurement from disparity a theoretical error analysis is presented, which provides an insight into the factors influencing the accuracy of the data. Experimental results show that the random error of depth measurement increases with increasing distance to the sensor, and ranges from a few millimeters up to about 4 cm at the maximum range of the sensor. The quality of the data is also found to be influenced by the low resolution of the depth measurements.

https://minerva-access.unimelb.edu.au/bitstream/handle/11343/225605/sensors-12-01437.pdf

Accuracy and Resolution of Kinect Depth Data for Indoor Mapping Applications

A self-scanned 1024 element photodiode array and minicomputer are used to measure the phase (wavefront) in the interference pattern of an interferometer to lambda/100. The photodiode array samples intensities over a 32 x 32 matrix in the interference pattern as the length of the reference arm is varied piezoelectrically. Using these data the minicomputer synchronously detects the phase at each of the 1024 points by a Fourier series method and displays the wavefront in contour and perspective plot on a storage oscilloscope in less than 1 min (Bruning et al. Paper WE16, OSA Annual Meeting, Oct. 1972). The array of intensities is sampled and averaged many times in a random fashion so that the effects of air turbulence, vibrations, and thermal drifts are minimized. Very significant is the fact that wavefront errors in the interferometer are easily determined and may be automatically subtracted from current or subsequent wavefrots. Various programs supporting the measurement system include software for determining the aperture boundary, sum and difference of wavefronts, removal or insertion of tilt and focus errors, and routines for spatial manipulation of wavefronts. FFT programs transform wavefront data into point spread function and modulus and phase of the optical transfer function of lenses. Display programs plot these functions in contour and perspective. The system has been designed to optimize the collection of data to give higher than usual accuracy in measuring the individual elements and final performance of assembled diffraction limited optical systems, and furthermore, the short loop time of a few minutes makes the system an attractive alternative to constraints imposed by test glasses in the optical shop.

Digital wavefront measuring interferometer for testing optical surfaces and lenses

PURPOSE\nTo measure macular choroidal thickness in normal eyes at different points using enhanced depth imaging (EDI) optical coherence tomography (OCT) and to evaluate the association of choroidal thickness and age.\n\n\nDESIGN\nRetrospective, observational case series.\n\n\nMETHODS\nEDI OCT images were obtained in patients without significant retinal or choroidal pathologic features. The images were obtained by positioning a spectral-domain OCT device close enough to the eye to acquire an inverted image. Seven sections were obtained within a 5 x 30-degree area centered at the fovea, with 100 scans averaged for each section. The choroid was measured from the outer border of the retinal pigment epithelium to the inner scleral border at 500-microm intervals of a horizontal section from 3 mm temporal to the fovea to 3 mm nasal to the fovea. Statistical analysis was performed to evaluate variations of choroidal thickness at each location and to correlate choroidal thickness and patient age.\n\n\nRESULTS\nThe mean age of the 30 patients (54 eyes) was 50.4 years (range, 19 to 85 years), and 14 patients (46.7%) were female. The choroid was thickest underneath the fovea (mean, 287 microm; standard deviation, +/- 76 microm). Choroidal thickness decreased rapidly in the nasal direction and averaged 145 microm (+/- 57 microm) at 3 mm nasal to the fovea. Increasing age was correlated significantly with decreasing choroidal thickness at all points measured. Regression analysis suggested that the subfoveal choroidal thickness decreased by 15.6 microm for each decade of life.\n\n\nCONCLUSIONS\nChoroidal thickness seems to vary topographically within the posterior pole. The thickness of the choroid showed a negative correlation with age. The decrease in the thickness of the choroid may play a role in the pathophysiologic features of various age-related ocular conditions.

Enhanced Depth Imaging Optical Coherence Tomography of the Choroid in Normal Eyes

Apparatus for mapping an object includes an illumination assembly, which includes a single transparency containing a fixed pattern of spots. A light source transilluminates the single transparency with optical radiation so as to project the pattern onto the object. An image capture assembly captures an image of the pattern that is projected onto the object using the single transparency. A processor processes the image captured by the image capture assembly so as to reconstruct a three-dimensional (3D) map of the object.

Depth mapping using projected patterns

A new method for eliminating the chromatic aberration of a diffractive optical element (DOE) for wideband wavelengths is presented. The wideband-wavelength diffractive optical element (WBDOE) consists of two aligned DOE's. The use of different dispersive materials for the two DOE's eliminates chromatic aberration. The design and simulation of a WBDOE for the visible spectrum are presented.

Design of a diffractive optical element for wide spectral bandwidth.

A method of wavefront (100) analysis including applying a transform to the wavefront, applying a plurality of different phase changes (110, 112, 114) to the transformed wavefront (108), obtaining a plurality of intensity maps (130, 132, 134) wherein the plurality of different phase changes are applied to region of the transformed wavefront, corresponding to a shape of the light source.

Spatial wavefront analysis and 3d measurement

A method for mapping includes projecting a pattern onto an object (28) via an astigmatic optical element (38) having different, respective focal lengths in different meridional planes (54, 56) of the element. An image of the pattern on the object is captured and processed so as to derive a three-dimensional (3D) map of the object responsively to the different focal lengths.

Distance-varying illumination and imaging techniques for depth mapping

A method for producing diffractive optical elements (DOE’s)
for multiple wavelengths without chromatic aberration is
described. These DOE’s can be designed for any distinct
wavelength. The DOE’s are produced from two different optical
materials, taking advantage of their different refractive indices and
dispersions.

Yoel Arieli

Papers

Depth mapping using projected patterns

Design of a diffractive optical element for wide spectral bandwidth.

Spatial wavefront analysis and 3d measurement

Distance-varying illumination and imaging techniques for depth mapping

Design of diffractive optical elements for multiple wavelengths