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Facial Muscle Anatomy-based Solution for Forensic Facial Reconstruction in Sri Lanka
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Facial Muscle Anatomy-based Solution for Forensic Facial Reconstruction in Sri Lanka
University of Colombo School of Computing (UCSC)
Research Team
Group Members : Anuradha.K MadugallaRoshan. N RajapakseIshari .U AmarasingheVinavi .H Padmathilake
Supervisors : Dr. Anuja DharmaratneMr. K D Sandaruwan
Dr. M.Vidanapathirana
Mass Disasters
Forensic Identification
End of Process
Problem Statement
Facial Reconstruction is not technically implemented in SriLanka due to :
Lack of Facial Tissue Thickness Data
Lack of Facial Feature Data
High Cost of Purchasable Solutions
Even the Manual Method is not implemented due to :
Requires a lot of time
Less productive
Lack of Expertise
The Objectives
To introduce a feasible Computer based three dimensional facial reconstruction solution to Sri Lanka
To ConductTissue Thickness AnalysisFacial Component Analysis; for the First time in Sri Lanka
Facial Reconstruction Types
Facial Reconsturction
2D Reconstruction
Manual Sketch
Computer assisted Sketch
3D Reconstruction
Manual Methods
Anthropometrical Anotomical
Combination
3D computer graphics based
Modeling
Sparse Approach
Dense Approach
The Manual Method
1. Anthropometrical2. Anatomical
Abate, A. et al. (2004) FACES: 3D Facial reConstruction from anciEnt Skulls using
content based image retrieval. Journal of Visual Languages and Computing, vol. 15, pp. 373-389.
3D computer graphics based Modeling
Andersson B. and Valfridsson M.(2005) Digital 3D Facial Reconstruction Based on Computed Tomography, Masters Thesis, Linkopings University
Davy et al. (2005) Computer-Graphic Facial Reconstruction:Forensic facial reconstruction using computer modelling software. Elsevier, pp.183-194.
Semi-Automation
Reconstruction Method Advantages Disadvantages
Manual Reconstruction
Natural looking reconstructed face
Manual Skull models Clay sculpting
Automated Reconstruction
Quick skull models Clay material not
needed
Unrealistic Reconstructed Face
Our Solution-Semi Automated Reconstruction
Natural looking reconstructed face
Quick skull models Clay material not
needed
Pre-requisite : Forensic AnalysisStep 01 : Acquiring the 3D modelStep 02 : Placement of LandmarksStep 03 : Digitally Sculpting the FaceStep 04 : Adding Facial Components
Solution Design
Pre Requirement: Skull Analysis
Determine
Sex
Age
Performed by
Forensic Analysts
Step 01:Skull Input
3D Scanner(Konica Minolta VIVID 910)
CT Scan (DICOM)
Step 02:Skin Depth Markers
Face Building
Studying Facial Muscle Anatomy
Step 03: Procedure of Face Creation
Step 04: Adding different Facial components/ Features
Most common Facial Features- Facial Component Analysis
The Process
3D Editing Software Digital Sculpting Software
Analysis performed Locally
Tissue Thickness Analysis Length of Landmarks
Facial Feature Analysis - Most common Facial Features of Sri Lankans
No data on Sri Lankans
Tissue Thickness Data Gathering Procedure
Department of Radiology at
Colombo South Teaching Hospital
Central Hospital (Pvt) Ltd
Durdans Hospital (Pvt) Ltd
Age range: From 20 to 30
Weight: Medium weight
Tissue Thickness Measuring
Different studies-different number of markers
Facial Tissue Thickness Analysis: Observations
Considerable difference between different races
Sri Lankans have greater tissue thicknesses at points 10, 19, 20 and 21
Hence, New Facial Tissue Thickness data gathering is needed- Sri LankanBased
Facial Component Analysis
Determine the most frequent indexes within the particular ageand gender
Conducted the survey
Age: 20 30 years
Sample: 500 male & female photographs
Components: Eyes and nose
The Process
Capture Skull
Add Markers Muscle Sculpting
Final Model
Tissue Thickness Analysis
Facial Feature Analysis
Case 01
Actual Photograph of the Deceased Reconstructed 3D Face Model
Case 02
Actual Photograph of the Deceased Reconstructed 3D Face Model
Case 03
CT rendered photograph of the patient Reconstructed 3D Face Model
Case 04
CT rendered photograph of the patient Reconstructed 3D Face Model
Evaluation Methods
Qualitative Methods
Face Pool Comparison
Quantitative Methods
Resemblance Rating
Assessment
Photogrammetry Analysis
Superimposition
Stephan CN and Henneberg M. Building faces from dry skulls: are they recognized above chance rates? J Forensic Sci 2001;46(3):432440.
Qualitative Methods : Face Pool Comparison
Qualitative Methods : Face Pool Comparison
http://facereconsurvey.appspot.com/
Results of Case 1
0 20 40 60 80 100
1st Person
2nd Person
3rd Person
4th Person
5th Person
Number of Votes %
Po
siti
on
of
the
Ph
oto
grap
h
Qualitative Methods : Face Pool Comparison
http://facereconsurvey2.appspot.com/
Results of Case 2
0 20 40 60 80 100
1st Person
2nd Person
3rd Person
4th Person
Number of Votes %
Po
siti
on
of
the
Ph
oto
grap
h
Evaluation Methods
Qualitative Methods
Face Pool Comparison
Quantitative Methods
Resemblance Rating
Assessment
Photogrammetry Analysis
Superimposition
Quantitative Methods : Resemblance Rating Assessment
Not at all Similar1
Not Similar2
Identifiable3
Fairly Similar4
Very Similar5
Quantitative Methods : Resemblance Rating Assessment
http://facereconsurvey3.appspot.com/
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
Overall Face The Nose The Mouth General Shape of the face
De
gre
e o
f R
ese
mb
lan
ce
Results of Case 3
Quantitative Methods : Resemblance Rating Assessment
http://facereconsurvey4.appspot.com/
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
Overall Face Nose Mouth General Shape of the face
De
gre
e o
f R
ese
mb
lan
ce
Results of Case 4
Evaluation Methods
Qualitative Methods
Face Pool Comparison
Quantitative Methods
Resemblance Rating
Assessment
Photogrammetry Analysis
Superimposition
Quantitative Methods :Photogrammetry Analysis
Landmark Abbreviation
Midline landmarks
1 Nasion N
2 Subnasale Sn
3 Labrale superius Ls
4 Menton Me
Bilateral landmarks
5, 6 Endocanthion En
7, 8 Exocanthion Ex
9, 10 Alare Ala
11, 12 Cheilion Ch
Quantitative Methods :Photogrammetry Analysis
Results of Case 1
Quantitative Methods :Photogrammetry Analysis
Results of Case 3
Evaluation Methods
Qualitative Methods
Face Pool Comparison
Quantitative Methods
Resemblance Rating
Assessment
Photogrammetry Analysis
Superimposition
Quantitative Methods : Superimposition
Results of Case 1
Quantitative Methods : Superimposition
Results of Case 3
Uniqueness of Our Solution
Introducing Facial Reconstruction to Sri Lanka
A Novel Facial Muscle Sculpting based reconstruction method
Optimized Marker Placements
A Solution unique to Sri Lanka - Sri Lankan data (Tissue Thickness, Facial Feature) based solution
Objectives Achieved
Problem 01 :
Lack of Tissue thickness data on Sri Lankans
Solution
Formulated a Facial Tissue Thickness model for Sri Lankans
Problem 02 :
Lack of Facial Feature data on Srilankans
Solution
Carried out a Facial Feature Analysis on Sri Lankans
Objectives Achieved (Contd..)
Problem 03 :
Expert knowledge on facial reconstruction process
Solution
3D Sculpting based simplified process
Problem 04 :
Time Consuming (2-3 weeks)
Solution
Less time is required (4-5 hours)
Difficulties Faced
Difficulty in acquiring a photograph of the deceased for evaluation purposes
Non availability of tissue thickness data
Suggestions for Future Research
To conduct facial tissue thickness analysis within all the age groups in the Sri Lankan context
To carry out a facial component analysis among Sri Lankans including all the age ranges
To integrate the facial reconstruction methodology with the missing persons database
Archaeological studies
The way forward.
Separate tissue thickness research by a team of consultants
More digital sculptors
First Forensic Facial Reconstruction Unit for Sri Lanka
Concluding Remarks
Forensic Medical Officers
Police Investigators
Relatives and friends of the
Missing People
Archeologists
Thank You !!!