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首页> 外文期刊>International Journal of Social Robotics >Tracking and Modeling of Human Activity Using Laser Rangefinders
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Tracking and Modeling of Human Activity Using Laser Rangefinders

机译：使用激光测距柜跟踪和建模人类活动

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摘要

We describe a system that uses laser rangefinders to track the positions of people in typical environments and then builds predictive models of the observed movement patterns and interactions between persons. We represent all human activity as detected by the laser rangefinder system as a probability distribution over the space of possible displacements. The assumption is that different activities will map to distinct probability distributions. Position tracks are first segmented and clustered into short sequences representing different activities. The sequence of activity clusters is then used to build a stochastic model of the observed movement patterns and the typical frequency of occurrence. Interactions are assumed to occur between persons whose corresponding probability distributions exhibit a high degree of similarity. We describe the performance of the system on data recorded from unscripted activities that occurred in different environments: open layout laboratory, corridor, and an outdoor courtyard. In the laboratory environment, the system was able to detect interactions between people (ping-pong players) without utilizing a pre-defined model of specific interactions. In the courtyard environment, the system was able to flag a sudden increase in the number of people in the courtyard as an anomalous occurrence without any pre-defined concept of occupancy of the environment.
机译：我们描述了一种使用激光测距柜来跟踪典型环境中人们位置的系统，然后在观察到的运动模式和人与人之间的相互作用中建立预测模型。我们代表激光测距仪系统检测到的所有人类活动，作为可能位移的空间的概率分布。假设是不同的活动将映射到不同的概率分布。位置曲目首先将其分段并聚集成表示不同活动的短序列。然后使用活动簇序列来构建观察到的运动模式的随机模型和典型的发生频率。假设相应概率分布表现出高度相似度的人之间发生相互作用。我们描述了系统对从不同环境中发生的未学活动记录的数据的表现：开放式布局实验室，走廊和室外庭院。在实验室环境中，该系统能够在不利用特定互动的预定义模型的情况下检测人（Ping-Pong玩家）之间的相互作用。在庭院环境中，该系统能够突然增加庭院中的人数作为异常事件，没有任何预定义的环境占用概念。

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