On sequential Monte Carlo sampling methods for Bayesian filtering
Statistics and Computing
Skin-Color Modeling and Adaptation
ACCV '98 Proceedings of the Third Asian Conference on Computer Vision-Volume II
Wide-Range, Person- and Illumination-Insensitive Head Orientation Estimation
FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000
Comparative Study of Coarse Head Pose Estimation
MOTION '02 Proceedings of the Workshop on Motion and Video Computing
Multi-View Face Tracking with Factorial and Switching HMM
WACV-MOTION '05 Proceedings of the Seventh IEEE Workshops on Application of Computer Vision (WACV/MOTION'05) - Volume 1 - Volume 01
ICMI '05 Proceedings of the 7th international conference on Multimodal interfaces
Recognition of human head orientation based on artificial neural networks
IEEE Transactions on Neural Networks
Modeling focus of attention for meeting indexing based on multiple cues
IEEE Transactions on Neural Networks
Real-time face tracking and pose estimation with partitioned sampling and relevance vector machine
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
On the contextual analysis of agreement scores
Multimodal corpora
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The paper presents an evaluation of both head pose and visual focus of attention (VFOA) estimation algorithms in a meeting room environment. Head orientation is estimated using a Rao-Blackwellized mixed state particle filter to achieve joint head localization and pose estimation. The output of this tracker is exploited in an Hidden Markov Model (HMM) to estimate people's VFOA. Contrarily to previous studies on the topic, in our set-up, the potential VFOA of people is not restricted to other meeting participants only, but includes environmental targets (table, slide screen), which renders the task more difficult due to more ambiguity between VFOA target directions. By relying on a corpus of 8 meetings of 8 minutes on average featuring 4 persons involved in the discussion of statements projected on a slide screen, and for which head orientation ground truth was obtained using magnetic sensor devices, we thoroughly assess the performance of the above algorithms, demonstrating the validity of our approaches and pointing out to further research directions.