lie detection system using facial expressions
DESCRIPTION
Lie Detection System Using Facial Expressions. Nathan de la Cruz Supervisor: Mehrdad Ghaziasgar MENTORS: Dane Brown AND Diego Mushfieldt. Introduction. Background Research has found: More than 80% of women admit to occasionally telling “harmless half truths ”. - PowerPoint PPT PresentationTRANSCRIPT
NATHAN DE LA CRUZ
SUPERVISOR: MEHRDAD GHAZIASGAR
MENTORS: DANE BROWN AND DIEGO MUSHFIELDT
Lie Detection System Using Facial Expressions
Introduction
BackgroundResearch has found:More than 80% of women admit to occasionally
telling “harmless half truths”.
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.
Ways to detect Lies
Study body language
Ways to detect Lies
Studying Eye movements
LIE TRUTH
Ways to detect Lies
Observing micro-expressions
User Requirements
The user requires the system to accurately tell if a person is or is not lying.
The user should be able to initialize the software.The user will ask the subject a series of questions.The software should be monitoring the subjects’
response. At any time the user should be able to stop the
processing and get a result.
Requirements Analysis
What Is Needed?
A Web Camera
A PC with Open Computer Vision (OpenCV) libraries Installed.
Requirements Analysis
Complete Analysis
Process Initialization (Clicking Some Button)Capturing Video In Real Time & Detecting The
FacePre-processing FramesProcessing Frames Using Optical FlowProcess Termination (Clicking Some Button)Displaying Information to User
Requirements Analysis
Capturing Video In Real Time & Detecting The Face
Requirements Analysis
Pre-processing FramesGreyscale Cropping
Requirements Analysis
Processing Frames Using Optical Flow
Displaying Information to User
• Either a “Passed” or a “Failed” message will be displayed
• User not faced with detailed information
• Improves the user understandability aspect of the software
Requirements Analysis
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
References
1. Robert Etherson. (2008). people admit to lying on their resumes. Available: http://www.databaserecords.com/blog/31-of-people-admit-to-lying-on-their-resumes/. Last accessed 28th March 2013.
2. Michelle Adler. (2009). little white coat lies. Available: http://www.newsweek.com/2009/01/07/little-white-coat-lies. Last accessed 28th March 2013.
3. Henry Bach . (2004). read face deciphering micro-expression. Available: http://www.divinecaroline.com/22189/83672-read-face-deciphering-microexpressions. Last accessed 28th March 2013.