Iccv2009 recognition and learning object categories p1 c02 - detecting single objects in context

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Context for single object classes

Who needs context anyway?We can recognize objects even out of context

Banksy

Why is context important?• Changes the interpretation of an object (or its function)

• Context defines what an unexpected event is

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.

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)

What is the context for a single object category?

The influence of an object extends beyond its physical boundaries

Global and local representationsbuilding

car

sidewalk

Urban street scene

Global and local representations

Image index: Summary statistics, configuration of textures

Urban street scene

features

histogram

building

car

sidewalk

Urban street scene

Global scene representations

Spatial structure is important in order to provide context for object localization

Sivic et. al., ICCV 2005Fei-Fei and Perona, CVPR 2005

Bag of words Spatially organized textures

Non localized textons

S. Lazebnik, et al, CVPR 2006Walker, Malik. Vision Research 2004 …

M. Gorkani, R. Picard, ICPR 1994A. Oliva, A. Torralba, IJCV 2001

An integrated model of Scenes, Objects, and Parts

Ncar

S

g

Scene

Scenegist

features

0

0

1

1

5

5

N

P(Ncar | S = street)

P(Ncar | S = park)

0 5 10 150

0.05

0.1

0.15

0.2

0 5 10 150

0.2

0.4

0.6

0.8

N

Context driven object detection

ZcarNcar

S

g

Scene

Scenegist

features

01 5

P(Ncar | S = street)

0 5 10 150

0.05

0.1

0.15

0.2

N

An integrated model of Scenes, Objects, and Parts

p(d | F=1) = N(d | m1, s1)p(d | F=0) = N(d | m0, s0)

We train a multiview car detector.

xcari

dcari

carFi

N=4

An integrated model of Scenes, Objects, and Parts

ZcarNcar

S

g

Scene

Scenegist

features

xcari

dcari

carFi

M=4

P(F,S | x,d,g) a p(F | S)p(S | g) p(xi | g) PN(xi; mb, sb2) PN(di; mtp, stp

2) PN(di; mtn, stn2)

i:Fi=0 i:Fi=1 i:Fi=0

A car out of context …

We are wired for 3D~6cm

We can not shut down 3D perception

(c) 2006 Walt Anthony

Scenes rule over objects

3D percept is driven by the scene, which imposes its ruling to the objects

3D from pixel valuesD. 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 Image"In ICCV workshop on 3D Representation for Recognition (3dRR-07), 2007.

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

Object Support

Slide by Derek Hoiem

Slide by James Coughlan

Slide by James Coughlan

3d Scene Context

Image World

Hoiem, Efros, Hebert ICCV 2005

3D scene context

meters

met

ers

Ped

Ped

Car

Hoiem, Efros, Hebert ICCV 2005

Qualitative Results

Initial: 2 TP / 3 FP Final: 7 TP / 4 FP

Local Detector from [Murphy-Torralba-Freeman 2003]

Car: TP / FP Ped: TP / FP

Slide by Derek Hoiem

3D City Modeling using Cognitive Loops

N. Cornelis, B. Leibe, K. Cornelis, L. Van Gool. CVPR'06

Single view metrologyCriminisi, et al. 1999

Need to recover:• Ground plane• Reference height• Horizon line• Where objects contact the ground