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8/8/2019 03 - Detecting Single Objects in Context
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C o n text fo r sin g leo b je ct cla sse s
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o nee s con ex anywayWe can recognize objects even out of
context
Banksy
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Why is context important?Changes the interpretation of an object (or its function)
Context defines what an unexpected event is
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Look-Alikes by Joan Steiner
,Even in high resolution we can not shut down contextual processing and
it is hard to recognize the true identities of the elements that compose.this scene
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The importance of context
Cognitive psychology Palmer 1975
Biederman 1981
Computer vision Noton and Stark (1971)
Hanson and Riseman (1978)
Barrow & Tenenbaum (1978) Ohta, kanade, Skai (1978)
Haralick (1983)
Strat and Fischler (1991)
Bobick and Pinhanez (1995)
Campbell et al (1997)
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What is the context for asingle object category?
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The influence of an objectextends beyond its physical
boundaries
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representations
building
car
sidewalk
Urban streetscene
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representations
: ,Image index Summary statisticsconfiguration of textures
Urban streetscene
features
histogram
building
car
sidewalk
Urban streetscene
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Global scenerepresentations
Spatial structure is important in order to provide context forobject localization
. .,Sivic et al ICCV 2005- ,Fei Fei and Perona CVPR 2005
Bag of words Spatially organized textures
Non localized textons
. , ,S Lazebnik et al CVPR 2006
, . Walker Malik Vision Research2004
. , . ,M Gorkani R Picard ICPR 1994
. , . ,A Oliva A Torralba IJCV 2001
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Context driven object detection
ZcarNcar
S
g
Scene
Scenegist
features
0 1 5
(P Ncar = )| S street
0
0.05
0.1
0.15
0.2
N
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,An integrated model of Scenes,Objects and Parts
( = ) =p d | F 1 N(d | 1, 1)
( = ) =p d | F 0 N(d | 0, 0)
. We train a multiview car detector
xcar
i
dcar
i
carF
i
=N 4
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,An integrated model of Scenes,Objects and Parts
ZcarNcar
S
g
Scene
Scenegist
features
xcar
i
dcar
i
carFi
=M 4
( , , , )F S | x d g ( ) ( ) (p F | S p S | g p xi )| g N(xi; b, b2) N(di; tp , tp 2)N(di; tn , tn
2) :i Fi=0 :i Fi=1 :i Fi=0
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A car out of context
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W e a re w ire d fo r
3 D ~6cm
We can not shut do n 3D
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We can not shut down 3Dperception
( )c 2006 Walt Anthony
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Scenes rule over objects
,3 D p e rce p t is d rive n b y th e sce n e w h ich im p o se s its ru lin g to th e
o b je cts
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3D from pixel values
. , . . , . , " - . .D Hoiem A A Efros and M Hebert Automatic Photo Pop up SIGGRAPH 2005
. , . , . . . " -A Saxena M Sun A Y Ng Learning 3 D Scene Structure from a Single Still Imag( - ), .In ICCV workshop on 3D Representation for Recognition 3dRR 07 2007
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Surface EstimationImage Support Vertical Sky
-V Left -V Center -V Right -V Porous -V Solid
[ , , ]Hoiem Efros Hebert ICCV 2005
ObjectSurface?
Support? Slide by Derek Hoiem
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Object Support
Slide by Derek Hoiem
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Slide by James Coughlan
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y J ug
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3d Scene Context
Image World
, ,Hoiem Efros Hebert ICCV 2005
3D t t
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3D scene context
meters
me
te
rs
Ped
Ped
Car
, ,Hoiem Efros Hebert ICCV 2005
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Qualitative Results
: /Initial 2 TP 3FP
: /Final 7 TP 4FP
[ - - ]Local Detector from Murphy Torralba Freeman 2003
:Car TP / FP :Ped TP / FP
Slide by Derek Hoiem
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3D City Modeling using CognitiveLoops
. , . , . , . .N C orne lis B Leibe K C orne lis L Van G ool C V PR '06
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Single view metrology, .C rim in isi e t a l 1 9 9 9
:N e e d to re cov e r G ro u n d p la n e R e fe re n ce h e ig h t H o rizo n lin e W h e re o b je cts co n ta ct th e
d