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Recognition of human emotion using sensor agent robot for interactive and adaptive living spaces

机译:使用传感器代理机器人识别交互式和自适应生活空间中的人类情绪

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Safer, more comfortable and energy-efficient living spaces are always demanded. However, most buildings are designed based on prescribed scenarios so that they do not act on abrupt changes of environments. We propose "Biofication of Living Spaces" that has functions of learning occupants' lifestyles and taking actions based on collected information. By doing so, we can incorporate the high adaptability to the building. Our goal is to make living spaces more "comfortable". However, human beings have emotion that implies the meaning of "comfortable" depends on each individual. Therefore our study focuses on recognition of human emotion. We suggest using robots as sensor agents. By using robots equipped with various sensors, they can interact with occupants and environment. We use a sensor agent robot called "e-bio". In this research, we construct a human tracking system and identified emotions of residents using their walking information. We focus on the influences of illuminance and sound. We classified emotions by calculating the distance of the mapped points in comfortable and uncomfortable spaces with parametric eigen space method, in which parameters are determined by a mapping of tracks in the space. As a method of pattern recognition, a weighted k-nearest neighbor is used. Experiments considering illuminance and sound environments, illustrates good correlation between emotion and environments.
机译:始终需要更安全,更舒适和节能的居住空间。但是,大多数建筑物是根据规定的方案设计的,因此它们不会对环境的突然变化起作用。我们提出“起居空间生物化”功能,该功能具有学习居住者的生活方式并根据收集到的信息采取行动的功能。通过这样做,我们可以将对建筑物的高度适应性纳入其中。我们的目标是使居住空间更加“舒适”。但是,人类的情感暗示着“舒适”的含义取决于每个人。因此,我们的研究集中在对人类情感的识别上。我们建议使用机器人作为传感器代理。通过使用配备有各种传感器的机器人,它们可以与乘员和环境互动。我们使用名为“ e-bio”的传感器代理机器人。在这项研究中,我们构建了一个人类跟踪系统,并使用居民的步行信息识别居民的情绪。我们专注于照度和声音的影响。我们通过使用参数本征空间方法计算舒适和不舒适空间中映射点的距离来对情绪进行分类,其中参数由空间中的轨迹映射确定。作为模式识别的方法,使用加权的k最近邻居。考虑照度和声音环境的实验说明了情绪与环境之间的良好关联。

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