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THE COST-TIST 283  Symmetry operators and their application in computer vision. Vito Di Gesù Cesare Valenti. Samia Bouchafa Bertrand Zavidovique. IEF University of Orsay France. DMA University of Palermo Italy.

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samia bouchafa bertrand zavidovique

THE COST-TIST 283 

Symmetry operators and their application in computer vision

Vito Di Gesù

Cesare Valenti

Samia Bouchafa

Bertrand Zavidovique

IEF

University of Orsay France

DMA

University of Palermo Italy

iAstro Workshop Granada 21-22 February 2002

symmetry and perception

Symmetry is a property that characterizes the invariance of a given system.

  • It is one of the most prominent spatial relations perceived by human beings.
  • Psychologists of perception, assign a relevant role to symmetry in attentive mechanism in both visual and auditory systems
  • Image segmentation
  • Object-parts representation and description
  • Detection of points of interest
Symmetry and perception

iAstro Workshop Granada 21-22 February 2002

computing symmetry

Computer vision tasks

global symmetry

local symmetry

Computation paradigm

edge

gray levels

hybrid

Computing Symmetry

iAstro Workshop Granada 21-22 February 2002

edge based computation
Edge Based Computation

Symmetry Axial Transform (SAT)(Blum, Nagel, 1978)

Smoothed Local Symmetry (SLS)(Brady, Asada, 1984)

Affine transformations and symmetry

(Mukhergee, Zisserman, Brady, Chan, Cipolla, 1995)

Partial occlusion(Sato, Cipolla, 1997)

String oriented approach

(Atallah, 1985), (Bruckstein and Shaked, 1995)

iAstro Workshop Granada 21-22 February 2002

gray levels approaches
Gray Levels Approaches

Texture analysis and symmetry measures

(Cheterikov and Haralick, 1995)

Measures based on the Radom’s transform

(Kiryati and Gofman, 1996)

Context free attentional operators(Reisfeld, Wolfson and Yeshurun 1995)

iAstro Workshop Granada 21-22 February 2002

symmetry transform di ges valenti 1994

Circular Symmetry

Symmetry TransformDi Gesù, Valenti, 1994

iAstro Workshop Granada 21-22 February 2002

discrete symmetry transform
Discrete Symmetry Transform

iAstro Workshop Granada 21-22 February 2002

slide9

Points of interest

iAstro Workshop Granada 21-22 February 2002

pyramid dst di ges valenti 1996
Pyramid-DST(Di Gesù,Valenti 1996)

Discrete Fourier Transform of D0 and

then:

iAstro Workshop Granada 21-22 February 2002

tracking problems
Tracking problems

iAstro Workshop Granada 21-22 February 2002

face analysis
Face analysis

Applications:security systems, criminology.

physical access control, man-machine interactions

iAstro Workshop Granada 21-22 February 2002

slide15

Expression analysis

Neutral, Sadness, Disgust, Happiness, Fear, Anger, Surprise

iAstro Workshop Granada 21-22 February 2002

object recognition systems chella di gesu infantino intravaia valenti 1997
Object recognition systemsChella, Di Gesu’, Infantino, Intravaia, Valenti 1997
  • Object Recognition Using Multiple Views
  • 3D shape reconstruction from image sequences

iAstro Workshop Granada 21-22 February 2002

iterated object transform di ges zavidovique 2002

Eoperator erosion

Iterated Object TransformDi Gesù, Zavidovique, 2002

The IOT computes the symmetry transform, T, on steadilyintensity reduced versions of the input image

iAstro Workshop Granada 21-22 February 2002

contrast change and level lines
Contrast change and level lines
  • Contrast change definition

Non-decreasing funtion g

  • Level set :
  • Contrast change impact
    • some level sets disappearance
    • no geometric deformation
  • Motion impact (+ noise)
    • some new level sets appearance
    • Geometric deformation
        • level lines crossing

iAstro Workshop Granada 21-22 February 2002

detection criteria
Detection criteria
  • How can we reconstruct the scene S ?
  • Possibilities for each line :

1. The line is present

        • no detection

2. The line is not present

        • Doubt :

Is the reference complete ?

Is the background uniform ?

3. The line crosses another one

        • detection

Week Detection

Strong Detection

iAstro Workshop Granada 21-22 February 2002

motion detection algorithm

Image Sequence

Reference

Updating

Level line Extraction

tracking of level lines

Characterization

Comparison

- Appearance of new lines

- Crossings between lines

Local Orientations

Detection

Motion detection algorithm

iAstro Workshop Granada 21-22 February 2002

level line characterization

Local characterization local orientation

Level line characterization
  • Two possibilities :

Global characterization surface, other moments of inertia, etc.

Associated level line

Our choice :local characterization

- Point detection

- No level lines occlusions management

iAstro Workshop Granada 21-22 February 2002

slide22

The result of the detection algorithm that is insensible towards contrast changes.

The original sequence presents some contrast changes due the automatic gain control of the camera and to natural scene illumination changes.

In the sequence, only points affected bymotion are displayed

iAstro Workshop Granada 21-22 February 2002

slide24

Fast Marching Methods and Level Set Methods are numerical techniques which can follow the evolution of interfaces. These interfaces can develop sharp corners, break apart, and merge together. The techniques have a wide range of applications, including problems in fluid mechanics, combustion, manufacturing of computer chips, computer animation, image processing, structure of snowflakes, and the shape of soap bubbles. These are two fundamentally different approaches to the problem of tracking moving interfaces, yet they share a common theory and numerical methodology.

iAstro Workshop Granada 21-22 February 2002

edge based computation1
Edge Based Computation

Symmetry Axial Transform (SAT)(Blum, Nagel, 1978)

iAstro Workshop Granada 21-22 February 2002

slide26

Smoothed Local Symmetry (SLS)

(Brady, Asada, 1984)

iAstro Workshop Granada 21-22 February 2002

slide27

Input

DST

Edge based operator

Yeshurun

iAstro Workshop Granada 21-22 February 2002

face analysis and algorithms cardaci di gesu intravaia 1998
Face analysis and algorithmsCardaci, Di Gesu’, Intravaia, 1998
  • The algorithm is based on an attentive architecture.
    • local and global symmetry operators
    • Reisfeld, Wolfson,Yeshurun (1995) Di Gesù, Valenti, Strinati, (1997)
    • graph theoretical algorithms Zhan (1972)
    • facial anatomy (model driven) Russel, (1994)

iAstro Workshop Granada 21-22 February 2002

slide30

Gelstat clustering (GC)

A relational graph (FG) is then built from the retrieved FC

Structural information are represented by a simple Internal Model (IM) based on psycho-visual correlation between components of face

Chen, Yachida (1996)

iAstro Workshop Granada 21-22 February 2002

results
Results

A sequence with global contrast changes

Séquence initiale

iAstro Workshop Granada 21-22 February 2002

slide32

Results

The same crossing junction but different lighting conditions

iAstro Workshop Granada 21-22 February 2002

slide33

Applications

Road environment

Vehicle/pedestrian detection and counting

Subway environment

Stationnary objects/human detection

iAstro Workshop Granada 21-22 February 2002

slide34

Comparisons

Level lines

Reference sequence

Six months before

Gradients orientation

Grey levels

Laplacian

iAstro Workshop Granada 21-22 February 2002

slide35

Comparisons

Gradient orientations

Problems with stability and thresholding !

iAstro Workshop Granada 21-22 February 2002