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Personal identification and visualization of relationships by using human trajectories

机译:使用人类轨迹对关系进行个人识别和可视化

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Good communication among workers helps make comfortable atmosphere in an office and contributes to the increase company productivity. Therefore, relationship between workers is an important information the manager needs to know by examining the worker's comfort level in an office environment. Moreover, the quantified information of the human relationship is useful for robots to provide services to working people in an office. There are many non-contact systems that can measure the positions of multiple persons in a room by using cameras and laser range sensors. However, who-is-who information is difficult to obtain in these systems without special devices, such as identification tags. This study proposes a personal identification method by using movement trajectories that are measured using cameras. Hidden Markov model is used to obtain who-is-who information. Moreover, visualization method of the relationship between workers is proposed based on the physical distance established among workers in an office throughout a day. The validity of the visualized relationships obtained by the proposed system is confirmed by comparing its results with that from self-evaluation questionnaires about a worker's strength of relationship with their co-workers.
机译:工人之间的良好沟通有助于在办公室营造舒适的氛围,并有助于提高公司的生产率。因此,工作人员之间的关系是经理在办公室环境中检查工作人员舒适度所需了解的重要信息。此外,人际关系的量化信息对于机器人向办公室中的工作人员提供服务很有用。有许多非接触式系统可以通过使用摄像头和激光测距传感器来测量房间中多个人的位置。但是,在没有特殊设备(例如识别标签)的情况下,很难在这些系统中获得谁是谁的信息。这项研究提出了一种通过使用相机测量的运动轨迹的个人识别方法。隐马尔可夫模型用于获取谁是谁的信息。此外,提出了一种基于一天中办公室中工人之间建立的物理距离的工人之间关系的可视化方法。通过将拟议系统获得的可视化关系的结果与有关工人与其同事之间的关系强度的自我评估调查表的结果进行比较,可以证实该可视化关系的有效性。

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