A Multi-Spectral Structured Light 3D Imaging System MATTHEW BEARDMORE MATTHEW BOWEN.
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Transcript of A Multi-Spectral Structured Light 3D Imaging System MATTHEW BEARDMORE MATTHEW BOWEN.
![Page 1: A Multi-Spectral Structured Light 3D Imaging System MATTHEW BEARDMORE MATTHEW BOWEN.](https://reader037.fdocuments.us/reader037/viewer/2022110405/56649ef65503460f94c0a841/html5/thumbnails/1.jpg)
A Multi-Spectral Structured Light 3D Imaging SystemMATTHEW BEARDMOREMATTHEW BOWEN
![Page 2: A Multi-Spectral Structured Light 3D Imaging System MATTHEW BEARDMORE MATTHEW BOWEN.](https://reader037.fdocuments.us/reader037/viewer/2022110405/56649ef65503460f94c0a841/html5/thumbnails/2.jpg)
Origins of our Project• Freshman Imaging Project
2011• Tasked with creating a 3D
imaging system over three quarters
• Presented at ImagineRIT 2012
• Contour distances along a person’s face gives information about the structure of that person’s trachea
• Uses technique known as Structured Light to scan subjects
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A brief primer on digital imaging
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Source: Digital Photography Presentation (Jeff Pelz, Joe Pow)
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How are digital images captured?• Light rays pass in through
an aperture
• Those rays are focused onto the sensor by a lens
• The sensor segments the light into individual boxes, known as pixels
• Each pixel interprets the intensity of the light striking it as a numerical value
A closeup of an imaging sensorSource: Digital Photography Presentation (Jeff Pelz, Joe Pow)
Individual pixel element
![Page 5: A Multi-Spectral Structured Light 3D Imaging System MATTHEW BEARDMORE MATTHEW BOWEN.](https://reader037.fdocuments.us/reader037/viewer/2022110405/56649ef65503460f94c0a841/html5/thumbnails/5.jpg)
What is Structured Light?• A 3D scanning technique• Involves projecting a series of
known patterns onto a subject
• A camera interprets the distortions in the patterns and calculates depth
• The series of patterns creates a temporal code for each pixel• Each projected pixel is
uniquely identified by this code
![Page 6: A Multi-Spectral Structured Light 3D Imaging System MATTHEW BEARDMORE MATTHEW BOWEN.](https://reader037.fdocuments.us/reader037/viewer/2022110405/56649ef65503460f94c0a841/html5/thumbnails/6.jpg)
What is Structured Light? (continued)• The camera can detect where
each projected pixel falls upon the subject• Interprets each pattern as a part
of a temporal code
• Combines each part at the end of the scan to reconstruct the temporal code
• Depth can then be calculated• Triangulation between camera
and projector projector
camera
projectedlight ray
reflectedlight ray
object beingscanned
p
Diagram source: Structured Light: The Mathematics of 3D Triangulation Presentation (Gabriel Taubin, Douglas Lanman)
![Page 7: A Multi-Spectral Structured Light 3D Imaging System MATTHEW BEARDMORE MATTHEW BOWEN.](https://reader037.fdocuments.us/reader037/viewer/2022110405/56649ef65503460f94c0a841/html5/thumbnails/7.jpg)
ImagineRIT 2012 Prototype
![Page 8: A Multi-Spectral Structured Light 3D Imaging System MATTHEW BEARDMORE MATTHEW BOWEN.](https://reader037.fdocuments.us/reader037/viewer/2022110405/56649ef65503460f94c0a841/html5/thumbnails/8.jpg)
![Page 9: A Multi-Spectral Structured Light 3D Imaging System MATTHEW BEARDMORE MATTHEW BOWEN.](https://reader037.fdocuments.us/reader037/viewer/2022110405/56649ef65503460f94c0a841/html5/thumbnails/9.jpg)
360° Scanning – Obstacles• Simultaneous scanning with black and white can cause
the scanners to interfere with each other
Left projector only Right projector only Both projectors simultaneously
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360° Scanning – Utilizing multiple spectra
Left projector displaying greenRight projector displaying red Camera with green color filter Camera with red color filter
• Instead of black and white scanning, different colors can be assigned to each camera-projector pair and isolated using color filters
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Our goals• Extend the original FIP2011 prototype to four cameras
and projectors• Allows for 360° + overhead scanning of subject (2π steradians)
• Utilize red, green, and blue portions of the visible spectrum• Allows for simultaneous projection, keeping scan times as short
as possible
• Decrease the overall scan time of our system• Assists in the scanning of subjects, as subjects will move less
![Page 12: A Multi-Spectral Structured Light 3D Imaging System MATTHEW BEARDMORE MATTHEW BOWEN.](https://reader037.fdocuments.us/reader037/viewer/2022110405/56649ef65503460f94c0a841/html5/thumbnails/12.jpg)
First attempt• Three color cameras, each with a Bayer filter on the
sensor
• Separate red, green, and blue channels into intensity maps (grayscale)• No color filters
• Suboptimal quality – projectors not displaying precise colors• E.g. displaying green would cause projector to display a small
amount of red
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Use of color filters• Instead of raw Bayer filter, color filters were placed in
front of camera and projector• Restricts projector output and camera input to only desired
wavelengths
• Significantly improved scanning results with three camera-projector pairs• Very little interference between scanners
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Adding an overhead scanner• Red, green, and blue make up primary colors of light• What color should the fourth scanner use?
• Yellow was chosen due to its distance away from any primary color relative to other secondary colors
• Significant interference due to breadth of wavelengths that the red and green filters cover• Yellow wavelength overlaps too much with red and green to be
viable
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Summer 2012 Prototype
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Results
•PUT PHOTO HERE
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Status of goals• Successfully implemented a multi-spectral scanner that
uses red, green, and blue to achieve 360° scanning
• Scan time halved from ~8 seconds to ~4 seconds
• Addition of fourth color – yellow – not successful• Colors filters not narrow enough to be useful for four scanners
• To achieve the goal of scanning a subject with the overhead view, the last camera-projector pair would not be able to scan simultaneously
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What we’ve learned • Matching the output of the projector to color filters is
difficult• Narrow matches are optimal
• Grayscale cameras paired with color filters provide optimal contrast and resolution• As opposed to the color (Bayer) cameras used in our project
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Acknowledgements• Chester F. Carlson Center for Imaging Science
• Joe Pow, Advisor
• Maria Helguera, Advisor
• Stefi Baum
• Class of Freshman Imaging Project 2011
• Gabriel Taubin and Douglas Lanman, Brown University