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System for multimodal data acquisition for human action recognition

机译：用于人类动作识别的多模式数据采集系统

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Multimodal data is being used more widely for human action recognition nowadays due to the progress of machine learning methods and the development of new types of sensors. The acquisition of the data required by such solutions is often troublesome, and it is difficult to find the proper tools for this process. In this paper, we present a new toolkit for multimodal acquisition. We address and discuss issues concerning the synchronization of data from multiple sensors, the optimization of the initial processing of raw data, and the design of the user interface for efficiently recording large databases. The system was verified in a setup consisting of three types of sensors - a Kinect 2, two PS3Eye cameras, and an accelerometer glove. The accuracy of the synchronization and performance of the initial processing proved to be suitable for human action acquisition and recognition. The system was used for the acquisition of an extensive database of sign language gestures. User feedback indicated the recording process to be efficient, which is also evaluated in the paper. The system is publicly available, both in the form of a standalone application as well as source code, and can be easily customized to any type of sensor setup.
机译：由于机器学习方法的进步和新型传感器的发展，如今多模式数据已被广泛用于人类动作识别。此类解决方案所需的数据获取通常很麻烦，并且很难找到适合此过程的工具。在本文中，我们提出了一种用于多模式采集的新工具包。我们解决并讨论了有关多个传感器的数据同步，原始数据的初始处理的优化以及有效记录大型数据库的用户界面设计的问题。该系统在由三种类型的传感器组成的设置中进行了验证：Kinect 2，两个PS3Eye相机和一个加速度计手套。同步的准确性和初始处理的性能证明适合于人类动作的获取和识别。该系统用于获取手语手势的广泛数据库。用户反馈表明记录过程是有效的，本文也对此进行了评估。该系统以独立应用程序和源代码的形式公开可用，并且可以轻松地针对任何类型的传感器设置进行定制。

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