“15 seconds of fame” use of computer vision in a modern art installation franc solina computer...
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“15 SECONDS OF FAME”Use of Computer Vision in a Modern Art Installation
Franc Solina
Computer Vision LaboratoryFaculty of Computer and Information ScienceUniversity of Ljubljana, Slovenia
Motivation for this work
collaboration with the Academy of Fine Arts in Ljubljana since 1995 new media, computer-based art installations (internet, virtual galleries, video, mobile robots, remote operation) work of scientist and conceptual artist Ken Goldberg, UC Berkeley (TELEGARDEN)
COMPUTER VISION + ART INSTALLATION = ?
Video cameras in art installations
wooden mirror (Daniel Rozin) touch me (Alba d’Urbano) liquid views (Monika Fleischman) … TECHNICAL LIMITATIONS: precise positioning of the subject
“In the future everybody will be famous for 15 minutes.”
Andy Warhol
Marilyn Monroe (Andy Warhol, 1964)
Image mediated culture
people like to look at themselves (mirrors, photos, paintings, video) vanity, self-discovery, self-assertion a face in mass culture -> FAME media attention - a mirror of the indivudual’s self-perception
WARHOL: celebrity photo -> portrait warhol-like portrait -> instant celebrity
Faces in computer vision
images of people find people, identify them, determine their activity video surveillance face recognition <- FACE DETECTION
15 seconds of fame
Hardware
Digital camera LCD monitor
computer
USB
Softwareinput photo
transformation color filters
pop-art portrait
illumination compensation learning
15 second loop
find faces +randomly select one
Roadmap
color-based face detection illumination compensation pop-art color transformations display and ordering of portraits over
the Internet conclusions
Our original face detection
Simplified face detection 1
Simplified face detection 2
ADVANTAGES: faster, detected also faces from profile
DISADVANTAGES: faces of dark complexion not detected, other body parts can be detected
Eliminating the influence of non-standard illumination
different from daylight illumination color constancy/compensation
methods
eestimate the present illumination reconstruct the image under standard
illumination run face detection algorithm
Color compensation methods
close to standard illumination low time complexity 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 counted only
once
White-Patch Retinex On each image white surface is present Illumination estimation: maximal color
Color compensation methods
NO GW
MGW RET
NO – original
GW – Gray World
MGW – Modified GW
RET – White-Patch Retinex
Color constancy methods
far from standard illumination Color by Correlation
(1) LEARNING: Take images of the Macbeth color checker under present illum. and under standard illum.
Use correlation to compute the transform. Parameters
(2) APPLY TRANSFORMATION
Color comp. + correll. method
NO GW MGW
RET COR
NO – original
GW – Gray World
MGW – Modified GW
RET – White-Patch Retinex
COR – Color by Correlation
Face detection results #1
0
20
40
60
80
100
standard incandescent flashlight neon
Without preprocessing GW MGW RET
Face detection after GW
GW
Face detection results #2
0
20
40
60
80
100
white yellow green blue red
Without preprocessing Color by Correlation
Face detection after COR
COR
Warhol’s celebrity portraits
segment the face from the background delineate the contours highlight some facial features (mouth, eyes,
hair) overlay with color screens
above transformations -> shape grammar BUT: requires automatic segmentation into
constituent face parts
pop-art color filters
+ color-balance
+ random coloring
+ posterize+ hue-saturation
+ color-balance+ posterize+ hue-saturation
= 17 universal filters
Display of portraits
4 smaller portraits same filter
different configurations 1 big portrait
each with a different filter
horizontal flip
each time a different person no detection -> last detected face with a
different pop-art filter 15 second counter
E-mail ordering of portraits
Ordering system
Beside the portrait is displayed an unique ID number
Sending e-mail [email protected]
Sending the requested picture
Creating of the web page
The gallery of “famous” people
from the project web page: black.fri.uni-lj.si/15sec
Audience interactions
people quickly realize that portraits of people present at the moment are displayed
if several people are present, becoming famous is elusive
subtle staging to get one’s most favourable image on the screen
subdued competition for “media” attention narcissistic and voyeristic use of the
“electronic mirror”
Exhibitions in art galleries
Forum Stadtpark, Graz, Austria, 19-26 Sep. 2003
Finzgar Gallery, Ljubljana, 14-26 Nov. 2002 8th International Festival of Computer Arts,
Maribor, 28 May-1 June 2002
Conclusions well accepted by the audience no visible interface a group of people can interact at once exact positioning of observers not necessary
• at least one face should be found in the input image• -> high percentage of true positive face detections• -> percentage of true negative face detections can be low• a huge database for testing face detection is generated
• The goal was not to mimic Andy Warhol’s portraits per se but to play upon the celebrification process and the discourse taking place in front of the installation.
From the first public showing
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