facial muscle anatomy

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


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


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



Resemblance Rating

Assessment


Superimposition

Quantitative Methods : Resemblance Rating Assessment

Not at all Similar1

Not Similar2

Identifiable3

Fairly Similar4

Very Similar5



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



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



Resemblance Rating

Assessment


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


Results of Case 1


Results of Case 3

Evaluation Methods

Qualitative Methods



Resemblance Rating

Assessment


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 !!!

facial muscle anatomy

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