What Is An Sls Camera

A structured-calorie-free 3D scanner is a 3D scanning device for measuring the iii-dimensional shape of an object using projected light patterns and a camera system.^[1]

Principle [edit]

Projecting a narrow band of lite onto a three-dimensionally shaped surface produces a line of illumination that appears distorted from other perspectives than that of the projector, and can exist used for geometric reconstruction of the surface shape (calorie-free section).

A faster and more versatile method is the projection of patterns consisting of many stripes at once, or of arbitrary fringes, as this allows for the acquisition of a multitude of samples simultaneously. Seen from different viewpoints, the pattern appears geometrically distorted due to the surface shape of the object.

Although many other variants of structured low-cal projection are possible, patterns of parallel stripes are widely used. The moving picture shows the geometrical deformation of a single stripe projected onto a simple 3D surface. The displacement of the stripes allows for an exact retrieval of the 3D coordinates of any details on the object's surface.

Generation of light patterns [edit]

Fringe blueprint recording system with 2 cameras (fugitive obstructions)

Two major methods of stripe pattern generation accept been established: Laser interference and projection.

The light amplification by stimulated emission of radiation interference method works with two broad planar laser beam fronts. Their interference results in regular, equidistant line patterns. Different blueprint sizes can be obtained by changing the angle between these beams. The method allows for the exact and like shooting fish in a barrel generation of very fine patterns with unlimited depth of field. Disadvantages are high toll of implementation, difficulties providing the ideal beam geometry, and laser typical effects like speckle noise and the possible self interference with beam parts reflected from objects. Typically, there is no means of modulating individual stripes, such as with Gray codes.

The project method uses incoherent light and basically works like a video projector. Patterns are usually generated by passing light through a digital spatial light modulator, typically based on ane of the three currently most widespread digital projection technologies, transmissive liquid crystal, cogitating liquid crystal on silicon (LCOS) or digital light processing (DLP; moving micro mirror) modulators, which have various comparative advantages and disadvantages for this application. Other methods of project could be and have been used, however.

Patterns generated by digital display projectors take small discontinuities due to the pixel boundaries in the displays. Sufficiently minor boundaries however can practically be neglected equally they are evened out past the slightest defocus.

A typical measuring assembly consists of one projector and at to the lowest degree one camera. For many applications, two cameras on opposite sides of the projector have been established as useful.

Invisible (or imperceptible) structured light uses structured calorie-free without interfering with other computer vision tasks for which the projected pattern volition exist confusing. Example methods include the use of infrared light or of extremely loftier framerates alternating between ii exact opposite patterns.^[2]

Calibration [edit]

A 3D scanner in a library. Scale panels can be seen on the right.

Geometric distortions past optics and perspective must exist compensated past a calibration of the measuring equipment, using special scale patterns and surfaces. A mathematical model is used for describing the imaging properties of projector and cameras. Essentially based on the simple geometric backdrop of a pinhole camera, the model likewise has to take into account the geometric distortions and optical aberration of projector and photographic camera lenses. The parameters of the camera as well equally its orientation in space can be adamant by a series of calibration measurements, using photogrammetric package adjustment.

Analysis of stripe patterns [edit]

There are several depth cues contained in the observed stripe patterns. The displacement of any single stripe tin can direct be converted into 3D coordinates. For this purpose, the private stripe has to be identified, which can for example exist accomplished by tracing or counting stripes (pattern recognition method). Another common method projects alternating stripe patterns, resulting in binary Gray code sequences identifying the number of each individual stripe hit the object. An of import depth cue also results from the varying stripe widths forth the object surface. Stripe width is a function of the steepness of a surface role, i.e. the first derivative of the elevation. Stripe frequency and stage deliver similar cues and tin be analyzed past a Fourier transform. Finally, the wavelet transform has recently been discussed for the same purpose.

In many practical implementations, series of measurements combining pattern recognition, Gray codes and Fourier transform are obtained for a complete and unambiguous reconstruction of shapes.

Another method besides belonging to the area of fringe projection has been demonstrated, utilizing the depth of field of the camera.^[three]

It is also possible to use projected patterns primarily equally a means of structure insertion into scenes, for an essentially photogrammetric acquisition.

Precision and range [edit]

The optical resolution of fringe projection methods depends on the width of the stripes used and their optical quality. It is as well limited by the wavelength of lite.

An extreme reduction of stripe width proves inefficient due to limitations in depth of field, camera resolution and display resolution. Therefore, the phase shift method has been widely established: A number of at to the lowest degree 3, typically about 10 exposures are taken with slightly shifted stripes. The first theoretical deductions of this method relied on stripes with a sine wave shaped intensity modulation, merely the methods piece of work with "rectangular" modulated stripes, as delivered from LCD or DLP displays also. Past phase shifting, surface detail of due east.g. 1/ten the stripe pitch tin can be resolved.

Current optical stripe design profilometry hence allows for detail resolutions down to the wavelength of lite, below 1 micrometer in do or, with larger stripe patterns, to approx. ane/10 of the stripe width. Concerning level accuracy, interpolating over several pixels of the acquired camera prototype can yield a reliable height resolution and also accuracy, down to 1/l pixel.

Arbitrarily large objects can be measured with appropriately big stripe patterns and setups. Applied applications are documented involving objects several meters in size.

Typical accuracy figures are:

• Planarity of a 2-pes (0.61 m) wide surface, to 10 micrometres (0.00039 in).
• Shape of a motor combustion chamber to 2 micrometres (7.9×x⁻⁵ in) (elevation), yielding a volume accuracy 10 times ameliorate than with volumetric dosing.
• Shape of an object 2 inches (51 mm) large, to about 1 micrometre (3.9×ten^−five in)
• Radius of a blade edge of e.k. 10 micrometres (0.00039 in), to ±0.4 μm

Navigation [edit]

Every bit the method tin can measure shapes from merely 1 perspective at a time, complete 3D shapes have to be combined from different measurements in dissimilar angles. This can be accomplished by attaching marker points to the object and combining perspectives afterwards by matching these markers. The process tin can be automated, past mounting the object on a motorized turntable or CNC positioning device. Markers can likewise be applied on a positioning device instead of the object itself.

The 3D data gathered can exist used to retrieve CAD (computer aided pattern) data and models from existing components (opposite engineering science), hand formed samples or sculptures, natural objects or artifacts.

Challenges [edit]

As with all optical methods, reflective or transparent surfaces raise difficulties. Reflections cause light to be reflected either away from the camera or right into its optics. In both cases, the dynamic range of the camera tin be exceeded. Transparent or semi-transparent surfaces as well cause major difficulties. In these cases, blanket the surfaces with a thin opaque lacquer just for measuring purposes is a common practice. A recent method handles highly reflective and specular objects by inserting a 1-dimensional diffuser between the low-cal source (e.g., projector) and the object to be scanned.^[iv] Alternative optical techniques have been proposed for handling perfectly transparent and specular objects.^[5]

Double reflections and inter-reflections tin cause the stripe pattern to be overlaid with unwanted light, entirely eliminating the chance for proper detection. Cogitating cavities and concave objects are therefore difficult to handle. Information technology is besides hard to handle translucent materials, such as skin, marble, wax, plants and homo tissue because of the phenomenon of sub-surface scattering. Recently, there has been an endeavour in the computer vision customs to handle such optically complex scenes past re-designing the illumination patterns.^[6] These methods have shown promising 3D scanning results for traditionally difficult objects, such as highly specular metal concavities and translucent wax candles.^[vii]

Speed [edit]

Although several patterns accept to be taken per picture in most structured lite variants, high-speed implementations are bachelor for a number of applications, for instance:

• Inline precision inspection of components during the production process.
• Health care applications, such as live measuring of human body shapes or the micro structures of human skin.

Motion picture applications accept been proposed, for case the conquering of spatial scene data for iii-dimensional idiot box.

Applications [edit]

• Industrial Optical Metrology Systems (ATOS) from GOM GmbH utilize Structured Light technology to achieve high accuracy and scalability in measurements. These systems feature self-monitoring for calibration status, transformation accurateness, ecology changes, and part movement to ensure high-quality measuring data.^[8]
• Google Projection Tango SLAM (Simultaneous localization and mapping) using depth technologies, including Structured Low-cal, Fourth dimension of Flying, and Stereo. Time of Flight crave the use of an infrared (IR) projector and IR sensor; Stereo does not.
• A technology by PrimeSense, used in an early version of Microsoft Kinect, used a pattern of projected infrared points to generate a dense 3D paradigm. (Later on, the Microsoft Kinect switched to using a time-of-flight camera instead of structured calorie-free.)
• Occipital
  • Structure Sensor uses a pattern of projected infrared points, calibrated to minimize distortion to generate a dense 3D image.
  • Structure Core uses a stereo camera that matches against a random pattern of projected infrared points to generate a dense 3D image.
• Intel RealSense camera projects a series of infrared patterns to obtain the 3D structure.
• Face ID system works by projecting more than than 30,000 infrared dots onto a face and producing a 3D facial map.
• VicoVR sensor uses a pattern of infrared points for skeletal tracking.
• Chiaro Technologies uses a unmarried engineered blueprint of infrared points chosen Symbolic Light to stream 3D indicate clouds for industrial applications
• Made to measure fashion retailing
• Paranormal investigation Ghost Hunting
• 3D-Automated optical inspection
• Precision shape measurement for production control (e.g. turbine blades)
• Reverse applied science (obtaining precision CAD data from existing objects)
• Book measurement (e.g. combustion chamber volume in motors)
• Nomenclature of grinding materials and tools
• Precision structure measurement of footing surfaces
• Radius determination of cutting tool blades
• Precision measurement of planarity
• Documenting objects of cultural heritage
• Capturing environments for augmented reality gaming
• Skin surface measurement for cosmetics and medicine
• Body shape measurement
• Forensic science inspections
• Road pavement structure and roughness
• Wrinkle measurement on material and leather
• Structured Illumination Microscopy
• Measurement of topography of solar cells^[9]
• 3D vision system enables DHL'southward e-fulfillment robot ^[10]

Software [edit]

• 3DUNDERWORLD SLS – Open up SOURCE^[eleven]
• DIY 3D scanner based on structured light and stereo vision in Python language^[12]
• SLStudio—Open Source Real Fourth dimension Structured Low-cal^[thirteen]

See as well [edit]

• Depth map
• Kinect
• Laser Dynamic Range Imager
• Lidar
• Low-cal stage
• Range imaging
• reflectance capture
• virtual cinematography

References [edit]

1. ^ Borko Furht (2008). Encyclopedia of Multimedia (second ed.). Springer. p. 222. ISBN978-0-387-74724-8.
2. ^ Fofi, David; T. Sliwa; Y. Voisin (Jan 2004). "A Comparative Survey on Invisible Structured Light" (PDF). SPIE Electronic Imaging — Motorcar Vision Applications in Industrial Inspection XII. San Jose, USA. pp. 90–97.
3. ^ "Tiefenscannende Streifenprojektion (DSFP) mit 3D-Kalibrierung". University of Stuttgart (in German). Archived from the original on 9 Apr 2013.
4. ^ Shree Thou. Nayar and Mohit Gupta, Lengthened Structured Lite, Proc. IEEE International Briefing on Computational Photography, 2012
5. ^ Eron Steger & Kiriakos Due north. Kutulakos (2008). "A Theory of Refractive and Specular 3D Shape by Lite-Path Triangulation". Int. J. Computer Vision, vol. 76, no. 1.
6. ^ Mohit Gupta, Amit Agrawal, Ashok Veeraraghavan and Srinivasa Yard. Narasimhan (2011). "Measuring Shape in the Presence of Inter-reflections, Sub-surface Scattering and Defocus". Proc. CVPR. {{cite news}}: CS1 maint: multiple names: authors list (link)
7. ^ Mohit Gupta; Shree K. Nayar (2012). "Micro Phase Shifting". Proc. CVPR.
8. ^ "ATOS – Industrial 3D Scanning Technology". GOM GmbH . Retrieved 9 July 2018.
9. ^ W J Walecki, F Szondy and Thou Chiliad Hilali, "Fast in-line surface topography metrology enabling stress calculation for solar cell manufacturing for throughput in excess of 2000 wafers per hour" 2008 Meas. Sci. Technol. nineteen 025302 (6pp) doi:x.1088/0957-0233/19/2/025302
10. ^ "3D vision organisation enables DHL's eastward-fulfillment robot". The Robot Report. December 12, 2018.
11. ^ Kyriakos Herakleous & Charalambos Poullis (2014). "3DUNDERWORLD-SLS: An Open up-Source Structured-Light Scanning Organisation for Rapid Geometry Acquisition". arXiv:1406.6595 [cs.CV].
12. ^ Hesam H. (2015). "DIY 3D scanner based on structured light and stereo vision in Python linguistic communication".
13. ^ J. Wilm; et al. (2014). "SLStudio: Open up-source framework for real-time structured light". doi:10.1109/IPTA.2014.7002001.

Sources [edit]

• Fechteler, P., Eisert, P., Rurainsky, J.: Fast and High Resolution 3D Face Scanning Proc. of ICIP 2007
• Fechteler, P., Eisert, P.: Adaptive Colour Classification for Structured Light Systems Proc. of CVPR 2008
• Liu Kai, Wang Yongchang, Lau Daniel L., Hao Qi, Hassebrook Laurence One thousand. (2010). "Dual-frequency pattern scheme for high-speed 3-D shape measurement". Optics Express. eighteen (5): 5229–5244. Bibcode:2010OExpr..18.5229L. doi:10.1364/oe.18.005229. PMID 20389536. {{cite journal}}: CS1 maint: multiple names: authors list (link)
• Kai Liu, Yongchang Wang, Daniel Fifty. Lau, Qi Hao, Laurence G. Hassebrook: Gamma Model and its Assay for Stage Measuring Profilometry. J. Opt. Soc. Am. A, 27: 553–562, 2010
• Yongchang Wang, Kai Liu, Daniel 50. Lau, Qi Hao, Laurence M. Hassebrook: Maximum SNR Design Strategy for Phase Shifting Methods in Structured Light Illumination, J. Opt. Soc. Am. A, 27(9), pp. 1962–1971, 2010
• Peng T., Gupta S.Thousand. (2007). "Model and algorithms for bespeak cloud construction using digital projection patterns" (PDF). Journal of Calculating and Informatics in Engineering. 7 (4): 372–381. CiteSeerX10.i.one.127.3674. doi:10.1115/1.2798115.
• Hof, C., Hopermann, H.: Comparing of Replica- and In Vivo-Measurement of the Microtopography of Human Skin University of the Federal Military machine, Hamburg
• Frankowski, G., Chen, M., Huth, T.: Real-time 3D Shape Measurement with Digital Stripe Projection by Texas Instruments Micromirror Devices (DMD) Proc. SPIE-Vol. 3958(2000), pp. 90–106
• Frankowski, G., Chen, M., Huth, T.: Optical Measurement of the 3D-Coordinates and the Combustion Sleeping accommodation Volume of Engine Cylinder Heads Proc. Of "Fringe 2001", pp. 593–598
• C. Je, Due south. W. Lee, and R.-H. Park Colour-Stripe Permutation Pattern for Rapid Structured-Light Range Imaging. Optics Communications, Volume 285, Effect nine, pp. 2320–2331, May i, 2012.
• C. Je, S. West. Lee, and R.-H. Park. High-Contrast Colour-Stripe Pattern for Rapid Structured-Low-cal Range Imaging. Computer Vision – ECCV 2004, LNCS 3021, pp. 95–107, Springer-Verlag Berlin Heidelberg, May ten, 2004.
• Elena Stoykova, Jana Harizanova, Venteslav Sainov: Pattern Project Profilometry for 3D Coordinates Measurement of Dynamic Scenes. In: Three Dimensional Television, Springer, 2008, ISBN 978-3-540-72531-2
• Song Zhang, Peisen Huang: High-resolution, Real-time 3-D Shape Measurement (PhD Dissertation, Stony Brook Univ., 2005)
• Tao Peng: Algorithms and models for 3-D shape measurement using digital fringe projections (Ph.D. Dissertation, Academy of Maryland, Us. 2007)
• Due west. Wilke: Segmentierung und Approximation großer Punktwolken (Dissertation Univ. Darmstadt, 2000)
• Yard. Wiora: Optische 3D-Messtechnik Präzise Gestaltvermessung mit einem erweiterten Streifenprojektionsverfahren (Dissertation Univ. Heidelberg, 2001)
• Klaus Körner, Ulrich Droste: Tiefenscannende Streifenprojektion (DSFP) Academy of Stuttgart (further English language references on the site)
• R. Morano, C. Ozturk, R. Conn, S. Dubin, S. Zietz, J. Nissano, "Structured light using pseudorandom codes", IEEE Transactions on Pattern Assay and Machine Intelligence 20 (3)(1998)322–327

Further reading [edit]

• Fringe 2005, The fifth International Workshop on Automatic Processing of Fringe Patterns Berlin: Springer, 2006. ISBN iii-540-26037-4 ISBN 978-3-540-26037-0

Source: https://en.wikipedia.org/wiki/Structured-light_3D_scanner

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