samia bouchafa bertrand zavidovique
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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. - PowerPoint PPT PresentationTRANSCRIPT
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iAstro Workshop Granada 21-22 February 2002
Samia Bouchafa
Bertrand Zavidovique
THE COST-TIST 283
Symmetry operators and their application in computer vision
IEF University of Orsay France
Vito Di Gesù
Cesare Valenti
DMA University of Palermo Italy
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iAstro Workshop Granada 21-22 February 2002
Symmetry and perceptionSymmetry is a property that characterizes the invariance of a given system.
o It is one of the most prominent spatial relations perceived by human beings.
o Psychologists of perception, assign a relevant role to symmetry in attentive mechanism in both visual and auditory systems
o Image segmentation
o Object-parts representation and description
o Detection of points of interest
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iAstro Workshop Granada 21-22 February 2002
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iAstro Workshop Granada 21-22 February 2002
Computing Symmetry
Computation paradigm
edge gray levels hybrid
global symmetry
Computer vision tasks
local symmetry
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iAstro Workshop Granada 21-22 February 2002
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)
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iAstro Workshop Granada 21-22 February 2002
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)
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iAstro Workshop Granada 21-22 February 2002
Symmetry TransformDi Gesù, Valenti, 1994
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Circular Symmetry
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iAstro Workshop Granada 21-22 February 2002
Discrete Symmetry Transform
DEDTDDST
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srmhji ggE
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iAstro Workshop Granada 21-22 February 2002
Points of interest
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iAstro Workshop Granada 21-22 February 2002
Pyramid-DST(Di Gesù,Valenti 1996)
Discrete Fourier Transform of D0 and
yx)( , max0 then:
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0log
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t
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iAstro Workshop Granada 21-22 February 2002
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iAstro Workshop Granada 21-22 February 2002
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iAstro Workshop Granada 21-22 February 2002
Tracking problems
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iAstro Workshop Granada 21-22 February 2002
Face analysisApplications:security systems, criminology. physical access control, man-machine interactions
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iAstro Workshop Granada 21-22 February 2002
Expression analysisNeutral, Sadness, Disgust, Happiness, Fear, Anger, Surprise
Neutral SmilingNeutral 92% 8%Smiling 20% 80%
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iAstro Workshop Granada 21-22 February 2002
Object recognition systems Chella, Di Gesu’, Infantino, Intravaia, Valenti 1997
o Object Recognition Using Multiple Viewso 3D shape reconstruction from image sequences
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iAstro Workshop Granada 21-22 February 2002
Iterated Object TransformDi Gesù, Zavidovique, 2002
The IOT computes the symmetry transform, T, on steadily intensity reduced versions of the input image
11,
1,
mforDD
DD
mm
TETIOT
IOT
E operator erosion
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iAstro Workshop Granada 21-22 February 2002
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
Contrast change and level lines
)(SgI
SI
)p(/p II
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iAstro Workshop Granada 21-22 February 2002
How can we reconstruct the scene S ?
Possibilities for each line :1. The line is present
no detection2. 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
Detection criteria
SI
i
NIII
S
...10
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iAstro Workshop Granada 21-22 February 2002
Motion detection algorithm
Level line Extraction
Characterization
Updating
Comparison
Detection
Image Sequence
Reference
Local Orientations
tracking of level lines
- Appearance of new lines
- Crossings between lines
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iAstro Workshop Granada 21-22 February 2002
• Two possibilities :
Global characterization surface, other moments of
inertia, etc.
Local characterization local orientation
100 Associated level line
Level line characterization
Our choice : local characterization- Point detection
- No level lines occlusions management
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iAstro Workshop Granada 21-22 February 2002
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 by motion are displayed
The result of the detection algorithm that is insensible towards contrast changes.
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iAstro Workshop Granada 21-22 February 2002
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iAstro Workshop Granada 21-22 February 2002
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.
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iAstro Workshop Granada 21-22 February 2002
Edge Based Computation
Symmetry Axial Transform (SAT) (Blum, Nagel, 1978)
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iAstro Workshop Granada 21-22 February 2002
Smoothed Local Symmetry (SLS)
(Brady, Asada, 1984)
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iAstro Workshop Granada 21-22 February 2002
DST
Edge based operatorYeshurun
Input
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iAstro Workshop Granada 21-22 February 2002
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)
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iAstro Workshop Granada 21-22 February 2002
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iAstro Workshop Granada 21-22 February 2002
Gelstat clustering (GC)
Structural information are represented by a simple Internal Model (IM) based on psycho-visual correlation between components of face Chen, Yachida (1996)
A relational graph (FG) is then built from the retrieved FC
Neutral SmilingNeutral 92% 8%Smiling 20% 80%
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iAstro Workshop Granada 21-22 February 2002
Séquence initiale
ResultsA sequence with global contrast changes
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iAstro Workshop Granada 21-22 February 2002
Results
The same crossing junction but different lighting conditions
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iAstro Workshop Granada 21-22 February 2002
ApplicationsRoad environment
Vehicle/pedestrian detection and counting
Subway environment
Stationnary objects/human detection
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iAstro Workshop Granada 21-22 February 2002
Comparisons
Reference sequence Six months before Level lines
Grey levels Laplacian Gradients orientation
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iAstro Workshop Granada 21-22 February 2002
Comparisons
Gradient orientations
Problems with stability and thresholding !