03 - Detecting Single Objects in Context

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

03 - Detecting Single Objects in Context

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