Modeling focus of attention for meeting indexing

R. Stiefelhagen, Jie Yang, A. Waibel
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引用次数: 60

Abstract

Visual cues, such as gesturing, looking at each other or monitoring each others facial expressions, play an important role in meetings. Such information can be used for indexing of multimedia meeting recordings. In this paper, we present an approach to detect who is looking at whom during a meeting. Our proposal is to employ Hidden Markov Models to characterize participants’ focus of attention by using gaze information as well as knowledge about the number and positions of people present in a meeting. The number and positions of the participants faces are detected in the field of view of a panoramic camera. We use neural networks to estimate the directions of participants’ gaze from camera images. We discuss the implementation of the approach in detail including system architecture, data collection, and evaluation. The system has achieved an accuracy rate of up to 93 % in detecting focus of attention on test sequences taken from meetings. We have used focus of attention as an index in a multimedia meeting browser.
会议索引的关注焦点建模
视觉暗示,比如打手势、互相看对方或观察对方的面部表情,在会议中发挥着重要作用。这些资料可用于多媒体会议记录的索引。在本文中,我们提出了一种方法来检测谁在会议期间看着谁。我们的建议是使用隐马尔可夫模型,通过使用注视信息以及关于会议中在场人员的数量和位置的知识来表征参与者的注意力焦点。参与者面部的数量和位置在全景相机的视野中被检测到。我们使用神经网络从相机图像中估计参与者的注视方向。我们详细讨论了该方法的实现,包括系统架构、数据收集和评估。该系统在检测来自会议的测试序列的注意力焦点方面的准确率高达93%。我们在多媒体会议浏览器中使用了焦点作为索引。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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