模式识别国家重点试验室-VideoLecturesNET

Facial

Expression

Analysis(CVPR’07&08)Static

Image

based

MethodsVideo

based

MethodsA

nature

facial

expression

evolves

over

timefrom

the

onset,

the

apex,

to

the

offset.The

key

issue

is

how

todescribe

thedynamics

of

the

expression?Facial

Expression

1National

Laboratory

of

Pattern

RecognitionInstitute

of

Automation,

Chinese

Academy

of

Sciences模式识别国家重点实验室中国科学院自动化研究所Video

based

MethodsThe

time-resolution

issueFacial

Expression

Analysis

(CVPR’

0National

Laboratory

of

Pattern

RecognitionInstitute

of

Automation,

Chinese

Academy

of

Sciences模式识别国家重点实验室中国科学院自动化研究所Facial

Expression

2Our

SolutionHarr-like

feature

representationernGaussian

based

temporal

pattmodelsFacial

Expression

Analysis

(CVPR’

0National

Laboratory

of

Pattern

RecognitionInstitute

of

Automation,

Chinese

Academy

of

Sciences模式识别国家重点实验室中国科学院自动化研究所Facial

Expression

3Our

SolutionDynamic

binary

patternsAdaboost

based

classifierFacial

Expression

Analysis

(CVPR’

0National

Laboratory

of

Pattern

RecognitionInstitute

of

Automation,

Chinese

Academy

of

Sciences模式识别国家重点实验室中国科学院自动化研究所Facial

Expression

4Facial

Expression

Analysis

(CVPR’

0模式识别国家重点实验室模式识别国家重点实验室ationalational

LaboratoryLaboratory

ofof

PatternPattern

RecognitionRecognitionNInstitute

of

Automation,

Chinese

Academy

of

Sciences中国科学院自动化研究所Facial

Expression

5Facial

Expression

Analysis

(CVPR’

0模式识别国家重模式识别国家重aboratoryaboratory

ofof

PatternPattern

RecognitionRecognitionNational

LInstitute

of

Automation,

Chinese

Academy

of

Sciences点实验室中国科学院自动化研究所Facial

Expression

6Face

Alignment

(ICCV’07)Face

Alignment

1.Active

Shape

Model

(ASM)The

original

ASMPCA

based

global

shape

modelLocal

texture

models

for

every

shape

pointThe

issuesPoints

are

independent

in

searchGlobal

shape

model

is

linearNational

Laboratory

of

Pattern

RecognitionInstitute

of

Automation,

Chinese

Academy

of

Sciences模式识别国家重点实验室中国科学院自动化研究所Component

based

FrameworkLocal

model:

PCA

+

Nearest

neighborhood

constrain

betweenpointsGlobal

model:

GPLVMFace

Alignment

(ICCV’07)National

Laboratory

of

Pattern

RecognitionInstitute

of

Automation,

Chinese

Academy

of

Sciences模式识别国家重点实验室中国科学院自动化研究所Face

Alignment

2.Objective

FunctionFace

Alignment

(ICCV’07)Face

Alignment

3.National

Laboratory

of

Pattern

RecognitionInstitute

of

Automation,

Chinese

Academy

of

Sciences模式识别国家重点实验室中国科学院自动化研究所MRF

based

Local

SearchFace

Alignment

(ICCV’07)Face

Alignment

4.National

Laboratory

of

Pattern

RecognitionInstitute

of

Automation,

Chinese

Academy

of

Sciences模式识别国家重点实验室中国科学院自动化研究所GPLVM

based

Global

ConstrainFace

Alignment

(ICCV’07)Face

Alignment

5.National

Laboratory

of

Pattern

RecognitionInstitute

of

Automation,

Chinese

Academy

of

Sciences模式识别国家重点实验室中国科学院自动化研究所GPLVM

vs.

PCA

as

Global

Model?Face

Alignment

(ICCV’07)National

Laboratory

of

Pattern

RecognitionInstitute

of

Automation,

Chinese

Academy

of

Sciences模式识别国家重点实验室中国科学院自动化研究所Face

Alignment

6.Face

Alignment

(ICCV’07)Alignment

Results

with

OcclusionASMPCMNOurmethodNational

Laboratory

of

Pattern

RecognitionInstitute

of

Automation,

Chinese

Academy

of

Sciences模式识别国家重点实验室中国科学院自动化研究所Face

Alignment

7.Face

Alignment

(ICCV’07)Alignment

Results

with

exaggerated

expression

and

off-rotationsASMPCMNOurmethodNational

Laboratory

of

Pattern

RecognitionInstitute

of

Automation,

Chinese

Academy

of

Sciences模式识别国家重点实验室中国科学院自动化研究所Face

Alignment

8.Face

Alignment

(ICCV’07)NationalNational

LaboratoryLaboratory

ofof

PatternPattern

RecognitRecognition模式识别国家重点实验室中国科学院自动化研究所Institute

of

Automation,

Chinese

Academy

of

SciencesFace

Alignment

9.Face