Socializing the intelligent tutor: bringing empathy to computer tutors
Learning Issues for Intelligent Tutoring Systems
The Journal of Machine Learning Research
Robust Real-Time Face Detection
International Journal of Computer Vision
How tutors characterize students: a study of personal constructs in tutoring
ICLS '96 Proceedings of the 1996 international conference on Learning sciences
Body Language Based Individual Identification in Video Using Gait and Actions
ICISP '08 Proceedings of the 3rd international conference on Image and Signal Processing
Optimised Meeting Recording and Annotation Using Real-Time Video Analysis
MLMI '08 Proceedings of the 5th international workshop on Machine Learning for Multimodal Interaction
Sensors Model Student Self Concept in the Classroom
UMAP '09 Proceedings of the 17th International Conference on User Modeling, Adaptation, and Personalization: formerly UM and AH
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Emotional intelligence is a clear factor in education [1–3], health care [4], and day to day interaction With the increasing use of computer technology, computers are interacting with more and more individuals This interaction provides an opportunity to increase knowledge about human emotion for human consumption, well-being, and improved computer adaptation. This research makes five main contributions 1) Construct a method for determining a set of sensor features that can be automatically processed to predict human emotional changes in observed people 2) Identify principles, algorithms, and classifiers that enable computational recognition of human emotion 3) Apply this method to an intelligent tutoring system instrumented with sensors 4) Apply and adapt the method to audio and video sensors for a number of applications such as a) detection of psychological disorders, b) detection of emotional changes in health care providers, c) detection of emotional impact of one person on another during video chat, and/or d) detection of emotional impact of one fictional character on another in a motion picture 5) Integrate emotional detection technologies so that they can be used in more realistic settings.