Some computer science issues in ubiquitous computing
Communications of the ACM - Special issue on computer augmented environments: back to the real world
Affective computing
FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000
Affective computing: challenges
International Journal of Human-Computer Studies - Application of affective computing in human—Computer interaction
A Fast Multi-Modal Approach to Facial Feature Detection
WACV-MOTION '05 Proceedings of the Seventh IEEE Workshops on Application of Computer Vision (WACV/MOTION'05) - Volume 1 - Volume 01
Multimodal affect recognition in learning environments
Proceedings of the 13th annual ACM international conference on Multimedia
Multimodal human-computer interaction: A survey
Computer Vision and Image Understanding
A Survey of Affect Recognition Methods: Audio, Visual, and Spontaneous Expressions
IEEE Transactions on Pattern Analysis and Machine Intelligence
iPhone as a physical activity measurement platform
CHI '10 Extended Abstracts on Human Factors in Computing Systems
User Modeling and User-Adapted Interaction
Affect Detection: An Interdisciplinary Review of Models, Methods, and Their Applications
IEEE Transactions on Affective Computing
IEEE Transactions on Affective Computing
Multimodal affect detection from physiological and facial features during ITS interaction
AIED'11 Proceedings of the 15th international conference on Artificial intelligence in education
Passive and In-Situ assessment of mental and physical well-being using mobile sensors
Proceedings of the 13th international conference on Ubiquitous computing
Recording affect in the field: towards methods and metrics for improving ground truth labels
ACII'11 Proceedings of the 4th international conference on Affective computing and intelligent interaction - Volume Part I
Out of the lab and into the fray: towards modeling emotion in everyday life
Pervasive'10 Proceedings of the 8th international conference on Pervasive Computing
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Affect detection has been widely advocated to be implemented in a natural environment. But due to constraints such as correct labeling and lack of usable sensors in natural environment most of the research in multi-modal affect detection has been done in laboratory environment. In this paper, we investigate affect detection in natural environment using sensors available in smart phones. We use facial expression and energy expenditure of a person to classify a person's affective state by continuously recording accelerometer data for energy and camera image for facial expression and measure the performance of the system. We have deployed our system in a natural environment and have provided special attention on annotation for the training data to validate the 'ground truth'. We have found important relationship between valence and arousal space for better accuracy of affect detection by using facial image and energy. This validates Russell's two dimensional theory of emotion using arousal and valence space. In this paper, we have presented initial findings in multi-modal affect detection. Using the multimodal technique, we propose a system that can be used in social networks for affect sensitive advertisement.