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
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NATHAN DE LA CRUZ
SUPERVISOR: MEHRDAD GHAZIASGAR
MENTORS: DANE BROWN AND DIEGO MUSHFIELDT
Lie Detection System Using Facial Expressions
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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.
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Ways to detect Lies
Study body language
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Ways to detect Lies
Studying Eye movements
LIE TRUTH
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Ways to detect Lies
Observing micro-expressions
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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.
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Requirements Analysis
What Is Needed?
A Web Camera
A PC with Open Computer Vision (OpenCV) libraries Installed.
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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
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Requirements Analysis
Capturing Video In Real Time & Detecting The Face
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Requirements Analysis
Pre-processing FramesGreyscale Cropping
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Requirements Analysis
Processing Frames Using Optical Flow
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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
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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
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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.