Illumination Independent Color-Based Face Detection “15 Seconds of Fame” Jure Kovač, Peter...
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![Page 1: Illumination Independent Color-Based Face Detection “15 Seconds of Fame” Jure Kovač, Peter Peer, Franc Solina Computer Vision Laboratory Faculty of Computer.](https://reader036.fdocuments.us/reader036/viewer/2022081603/56649e5e5503460f94b57afa/html5/thumbnails/1.jpg)
Illumination Independent Color-
Based Face Detection
“15 Seconds of Fame”
Jure Kovač, Peter Peer, Franc Solina
Computer Vision LaboratoryFaculty of Computer and Information ScienceUniversity of Ljubljana, Slovenia
![Page 2: Illumination Independent Color-Based Face Detection “15 Seconds of Fame” Jure Kovač, Peter Peer, Franc Solina Computer Vision Laboratory Faculty of Computer.](https://reader036.fdocuments.us/reader036/viewer/2022081603/56649e5e5503460f94b57afa/html5/thumbnails/2.jpg)
“In the future everybody will be famous for 15 minutes.”
Andy Warhol
Marilyn Monroe (Andy Warhol, 1964)
Application Contribution Illum. compensation Tested using our
algorithm Purpose
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An interactive art installation 15 second of fame
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Hardware
Digital camera LCD monitor
computer
USB
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Software
input photo
finding faces
transformation color filter
pop-art portrait
illumination compensation learning
15 second loop
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Roadmap
Face detection algorithm Illumination compensation
approaches Pop-art color transformations Summary
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Face detection method #1Our original face detection method
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Face detection method #2Simplified face detection method
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Eliminating the influence of non-standard illumination
Color descriptor Color
constancy/compensation Problem solving Method outline:
Estimate the present illumination
Reconstruct the image under standard illumination
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Close to standard illumination
Grey World Average surface color in the image is achromatic Illumination estimation: average color Mean gray value
Modified Grey World Illumination estimation: each color is count only
once
White-Patch Retinex On each image white surface is present Illumination estimation: maximal color
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Far from standard illumination
Color by Correlation Initial step: learning Illumination detection using correlation Illumination reconstruction using SPD data
(effective idea: use Macbeth color checker)
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Influence of methods #1
NO GW
MGW RET
NO – original
GW – Gray World
MGW – Modified GW
RET – White-Patch Retinex
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Influence of methods #2
NO GW MGW
RET COR
NO – original
GW – Gray World
MGW – Modified GW
RET – White-Patch Retinex
COR – Color by Correlation
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Face detection results #1
0
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standard incandescent flashlight neon
Without preprocessing GW MGW RET
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Face detection results #2
0
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white yellow green blue red
Without preprocessing Color by Correlation
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Effectiveness illustration #1
GW
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Effectiveness illustration #2
COR
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Color transformations
+ color-balance
+ random coloring
+ posterize+ hue-saturation
+ color-balance+ posterize+ hue-saturation
= 17 universal filters
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Conclusions
Very well accepted by the audience Accurate face detection method Robust face detection algorithm
(due to illumination compensation methods) Color transformations generate a pop-art effect Portrait can be ordered by e-mail
Different graphic effect according to the mood Additional filters (negative image, b&w
technique, highlighted edges,…) Extension to 3D?
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The gallery of famous people
from the project web page: black.fri.uni-lj.si/15sec
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The first public showing
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Illumination reconstruction