Linking public spaces: technical and social issues
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Privacy by Design - Principles of Privacy-Aware Ubiquitous Systems
UbiComp '01 Proceedings of the 3rd international conference on Ubiquitous Computing
Coding Facial Expressions with Gabor Wavelets
FG '98 Proceedings of the 3rd. International Conference on Face & Gesture Recognition
The language of privacy: Learning from video media space analysis and design
ACM Transactions on Computer-Human Interaction (TOCHI)
Tensions in designing capture technologies for an evidence-based care community
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
International Journal of Human-Computer Studies
The watcher and the watched: social judgments about privacy in a public place
Human-Computer Interaction
Face detection and tracking in video sequences using the modifiedcensus transformation
Image and Vision Computing
PAM: a photographic affect meter for frequent, in situ measurement of affect
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Proceedings of the 13th international conference on Ubiquitous computing
Mood Meter: large-scale and long-term smile monitoring system
ACM SIGGRAPH 2012 Emerging Technologies
MoodScope: building a mood sensor from smartphone usage patterns
Proceeding of the 11th annual international conference on Mobile systems, applications, and services
Whose "city of tomorrow" is it?: on urban computing, utopianism, and ethics
Proceedings of the 2nd ACM SIGKDD International Workshop on Urban Computing
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In this study, we created and evaluated a computer vision based system that automatically encouraged, recognized and counted smiles on a college campus. During a ten-week installation, passersby were able to interact with the system at four public locations. The aggregated data was displayed in real time in various intuitive and interactive formats on a public website. We found privacy to be one of the main design constraints, and transparency to be the best strategy to gain participants' acceptance. In a survey (with 300 responses), participants reported that the system made them smile more than they expected, and it made them and others around them feel momentarily better. Quantitative analysis of the interactions revealed periodic patterns (e.g., more smiles during the weekends) and strong correlation with campus events (e.g., fewer smiles during exams, most smiles the day after graduation), reflecting the emotional responses of a large community.