Principled design of the modern Web architecture
ACM Transactions on Internet Technology (TOIT)
Machine Learning
Head Pose Estimation in Computer Vision: A Survey
IEEE Transactions on Pattern Analysis and Machine Intelligence
Social signal processing: Survey of an emerging domain
Image and Vision Computing
Real time head pose estimation from consumer depth cameras
DAGM'11 Proceedings of the 33rd international conference on Pattern recognition
Real time head pose estimation with random regression forests
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
Random Forests for Real Time 3D Face Analysis
International Journal of Computer Vision
GAIN: web service for user tracking and preference learning - a smart TV use case
Proceedings of the 7th ACM conference on Recommender systems
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In this paper, we present our "work-in-progress" approach to implicitly track user interaction and infer the interest a user can have for TV media. The aim is to identify moments of attentive focus, noninvasively and continuously, to dynamicaly improve the user profile by detecting which annotated media have drawn the user attention. Our method is based on the detection and estimation of face pose in 3D using a consumer depth camera. This allows us to determine when a user is or not looking at his television. This study is realized in the scenario of second screen interaction (tablet, smartphone), a behavior that has become common for spectators. We present our progress on the system and its integration in the LinkedTV project.