Towards Recognising Collaborative Activities Using Multiple On-Body Sensors

被引:8
|
作者
Ward, Jamie A. [1 ]
Hevesi, Peter [1 ]
Pirkl, Gerald [1 ]
Lukowicz, Paul [1 ]
机构
[1] German Res Ctr Artificial Intelligence DFKI, Kaiserslautern, Germany
关键词
Wearable sensing; Datasets; Activity recognition;
D O I
10.1145/2968219.2971429
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
This paper describes the initial stages of a new work on recognising collaborative activities involving two or more people. In the experiment described a physically demanding construction task is completed by a team of 4 volunteers. The task, to build a large video wall. requires communication, coordination, and physical collaboration between group members. Minimal outside assistance is provided to better reflect the ad-hoc and loosely structured nature of real-world construction tasks. On-body inertial measurement units (IMU) record each subject's head and arm movements; a wearable eye-tracker records gaze and egocentric video; and audio is recorded from each person's head and dominant arm. A first look at the data reveals promising correlations between, for example, the movement patterns of two people carrying a heavy object. Also revealed are clues on how complementary information from different sensor types, such as sound and vision. might further aid collaboration recognition.
引用
收藏
页码:221 / 224
页数:4
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