Robust Real Time Face Tracking for the Analysis of Human Behaviour
Robust Real Time Face Tracking for the Analysis of Human Behaviour
复制标题
用于分析人类行为的强大实时面部跟踪
DOI：
10.1007/978-3-540-78155-4_1
复制
发表时间：
2007
期刊：
影响因子：
--
通讯作者：
N. Campbell
中科院分区：
文献类型：
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作者：
D. Douxchamps;N. Campbell
我们提出了一个实时系统的人脸检测，跟踪和表征从全方位的视频。使用Viola-Jones作为人脸检测的基础，然后应用各种滤波器来消除误报。使用基于颜色的跟踪来填充由Viola-Jones算法进行的两次人脸检测之间的间隙。该系统可以在室内和室外几个一小时的无约束会议视频中可靠地检测到超过97%的人脸，同时保持非常低的假阳性率（<0.05%），并且参数没有变化。不同的测量，如头部运动和身体活动的提取，以提供输入，以进一步研究人类行为和跟踪参与者的活动，在圆桌会议和类似的话语环境。
We present a real-time system for face detection, tracking and characterisation from omni-directional video. Viola-Jones is used as a basis for face detection, then various filters are applied to eliminate false positives. Gaps between two detection of a face by the Viola-Jones algorithms are filled using a colour-based tracking. This system reliably detects more than 97% of the faces across several one-hour videos of unconstrained meetings, both indoor and outdoor, while keeping a very low false-positive rate (<0.05%) and without changes in parameters. Diverse measurements such as head motion and body activity are extracted to provide input to further research on human behaviour and for tracking participant activites at round-table meetings and similar discourse environments.
DOI：
10.1007/11556985
发表时间：
2005
期刊：
--
影响因子：
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作者：
R. Moreno-Díaz;F. Pichler;Alexis Quesada Arencibia
通讯作者：
R. Moreno-Díaz;F. Pichler;Alexis Quesada Arencibia