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The Attention Tracking Tool (AT2) has reached a significant milestone, with the Task Matrix Requirements Document now available for viewing on the project website. This document outlines AT2’s features, including face detection, emotion measurement, and machine learning capabilities using OpenCV and EmguCV. The software has been tested in a classroom environment for real-time emotion detection and facial expression analysis. Comprehensive test plans and architectural designs are included, emphasizing the tool's reliability and performance metrics.
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Attention Tracking Tool October 3, 2011
Requirements Document • Now available to view on Project Website! • Description of AT2’s features and behaviors • Software & Libraries • Visual Studio 2010 • OpenCV 2.3 • EmguCV 2.2.1 • Microsoft .NET Framework 4.0
Learning OpenCV & EmguCV • Purchased PDF from O’Reilly • Looked at online tutorials • AT2 now on SVN http://attentiontrackingtool.googlecode.com/svn/trunk/ • Face detection implemented • GUI created • Video record in Progress
Emotion Detection Research • Strategy • Detect faces in group • Track faces on screen • Detect features of face for emotion • Measure changes in head position and features • Use measurements to determine emotion • Machine Learning • OpenCV Support for Machine Learning • AdaBoost, SVM, MLP, Naïve Beyes, Binary Trees
Test Plan • Available to view on Project Website! • Test software for every possible situation we might encounter • Attention Metrics • Presentation Record • Facial Expression • Tests on Live Subjects Approved by IRB! • Test application in actual classroom environment
Auto Camera Tracking System • Olin Engineering Auditorium • 2 camera • Lanyard • Our software • 1 camera • API
Design Document • Available to view on Project Website! • Architecture of System and Software Modules.