Lie Detection System Using Micro-Expressions

NATHAN DE LA CRUZ

SUPERVISOR: MEHRDAD GHAZIASGAR

MENTORS: DANE BROWN AND DIEGO MUSHFIELDT

Lie Detection System Using Micro-Expressions

A Quick Recap …

Background People are lied to constantly. Research has found:

31% of people admit to lying on their CV’s.60% of people lie at least once during a 10 minute

conversation and on average tell 2 to 3 lies.

Proposed Solution Create an interactive system that will detect a lie

using micro-expressions.

Project Design and Development

• User Interface Specification (UIS)• High Level Design (HLD)• Low Level Design (LLD)• Prototype (Demo)

User Interface Specification

The user interface as seen by the User

User Interface Specification

User interacts with the system via a mouse

How the User Interface behaves

Project Design and Development

• User Interface Specification (UIS)• High Level Design (HLD)• Low Level Design (LLD)• Prototype (Demo)

High Level Design (HLD)

Input

Image Processing

Classification Output

Capture

EventButton

Capture

EventButton

High Level Design (HLD)

Input

Video feed

Capture Images

Capture Event Button

Image Processing

Crop face

Convert to greyscale

Convert to Local Binary

Pattern Image

Classification

Support Vector

Machine (SVM)

Output

Display Text in Window

Project Design and Development

• User Interface Specification (UIS)• High Level Design (HLD)• Low Level Design (LLD)• Prototype (Demo)

Low Level Design (LLD)

Input –Video Feed

Capture from camera:

cvCaptureFromCAM();

Low Level Design (LLD)

Get Consecutive frames

Capture frame:

cvQueryFrame();

Low Level Design (LLD)

User Clicks on Button

cvSetMouseCallback ( );

Low Level Design (LLD)

Image Processing Width of eye pair x Height of face

Detect Face:

face_cascade.detectMultiScale();

Detect eyes:

eyes_cascade.detectMultiScale();

Low Level Design (LLD)

Image Processing Color Image to Greyscale Image

cvCvtColor(CV_RGB2GRAY)

Low Level Design (LLD)

Local Binary Patterns

OUTPUT

Low Level Design (LLD)

Output Display output in window

cvShowImage (“window”);

OR

Project Design and Development

• User Interface Specification (UIS)• High Level Design (HLD)• Low Level Design (LLD)• Prototype (Demo)

Prototype (Demo)

In this Demo I will:

Detect 2 Macro-Expressions i.e. Anger And Happy Detect 2 Micro-Expressions That are associated with

lying and fall under the category of Anger i.e. Narrowed Lips And Furrowed Brow

References

1. Paul Ekman Group, LLC. 2013. Paul Ekman Group, LLC. [ONLINE] Available at: http://www.paulekman.com. [Accessed 27 May 2013].

2. Micro Expressions - Research, Theory & Lying | Human Behaviour, Forensic Psychology | Blifaloo.com. 2013. Micro Expressions - Research, Theory & Lying | Human Behaviour, Forensic Psychology | Blifaloo.com. [ONLINE] Available at: http://www.blifaloo.com/info/microexpressions.php. [Accessed 27 May 2013].

3. Paul Ekman, 2007. Emotions Revealed, Second Edition: Recognizing Faces and Feelings to Improve Communication and Emotional Life. 2nd Edition. Holt Paperbacks.

Project Plan

Goal Due date• Learn to use OpenCV functions/tools to manipulate

images and videos• Requirements Gathering

End of Term1 (Completed)

Design and Development• Creating User Interface Specification• Designing structure of code• Identifying 2 micro-expressions and 2 macro-expression

End of Term2 (Completed)

Implementation• Training SVM to identify more micro-expressions• Optimizing LBP by altering the smoothing function

End of Term3

Testing and Evaluating• Collect more training data for SVM• Collect more test data for SVM End of Term4