Automatic Analysis of Facial Expressions: The State of the Art
IEEE Transactions on Pattern Analysis and Machine Intelligence
Robust Real-Time Face Detection
International Journal of Computer Vision
Participant Activity Detection by Hands and Face Movement Tracking in the Meeting Room
CGI '04 Proceedings of the Computer Graphics International
Face Authentication Test on the BANCA Database
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 4 - Volume 04
Evaluating Multi-Object Tracking
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops - Volume 03
Comparison of MLP and GMM classifiers for face verification on XM2VTS
AVBPA'03 Proceedings of the 4th international conference on Audio- and video-based biometric person authentication
Face verification using adapted generative models
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
The 2005 AMI system for the transcription of speech in meetings
MLMI'05 Proceedings of the Second international conference on Machine Learning for Multimodal Interaction
Browsing recorded meetings with ferret
MLMI'04 Proceedings of the First international conference on Machine Learning for Multimodal Interaction
Google home: Experience, support and re-experience of social home activities
Information Sciences: an International Journal
Using audio, visual, and lexical features in a multi-modal virtual meeting director
MLMI'06 Proceedings of the Third international conference on Machine Learning for Multimodal Interaction
| Hi-index | 0.00 |
The project Augmented Multi-party Interaction (AMI) is concerned with the development of meeting browsers and remote meeting assistants for instrumented meeting rooms – and the required component technologies R&D themes: group dynamics, audio, visual, and multimodal processing, content abstraction, and human-computer interaction. The audio-visual processing workpackage within AMI addresses the automatic recognition from audio, video, and combined audio-video streams, that have been recorded during meetings. In this article we describe the progress that has been made in the first two years of the project. We show how the large problem of audio-visual processing in meetings can be split into seven questions, like “Who is acting during the meeting?”. We then show which algorithms and methods have been developed and evaluated for the automatic answering of these questions.