Presentation on theme: "NATHAN DE LA CRUZ SUPERVISOR: MEHRDAD GHAZIASGAR MENTORS: DANE BROWN AND DIEGO MUSHFIELDT Lie Detection System Using Facial Expressions."— Presentation transcript:
NATHAN DE LA CRUZ SUPERVISOR: MEHRDAD GHAZIASGAR MENTORS: DANE BROWN AND DIEGO MUSHFIELDT Lie Detection System Using Facial Expressions
Introduction Background Research 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 LIETRUTH
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 Face Pre-processing Frames Processing Frames Using Optical Flow Process Termination (Clicking Some Button) Displaying Information to User
Requirements Analysis Capturing Video In Real Time & Detecting The Face
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 GoalDue 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: their-resumes/. Last accessed 28th March Michelle Adler. (2009). little white coat lies. Available: Last accessed 28th March Henry Bach. (2004). read face deciphering micro-expression. Available: microexpressions. Last accessed 28th March 2013.