McCowan Iain, Gatica-Perez Daniel, Bengio Samy, Lathoud Guillaume, Barnard Mark, Zhang Dong
IDIAP Research Institute, Rue du Simplon 4, CP 592, CH-1920 Martigny, Switzerland.
IEEE Trans Pattern Anal Mach Intell. 2005 Mar;27(3):305-17. doi: 10.1109/TPAMI.2005.49.
This paper investigates the recognition of group actions in meetings. A framework is employed in which group actions result from the interactions of the individual participants. The group actions are modeled using different HMM-based approaches, where the observations are provided by a set of audiovisual features monitoring the actions of individuals. Experiments demonstrate the importance of taking interactions into account in modeling the group actions. It is also shown that the visual modality contains useful information, even for predominantly audio-based events, motivating a multimodal approach to meeting analysis.
本文研究了会议中群体行为的识别。采用了一个框架，其中群体行为源于个体参与者之间的互动。使用基于不同隐马尔可夫模型（HMM）的方法对群体行为进行建模，其中观测值由一组监测个体行为的视听特征提供。实验证明了在对群体行为进行建模时考虑互动的重要性。研究还表明，即使对于主要基于音频的事件，视觉模态也包含有用信息，这激发了一种用于会议分析的多模态方法。
