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Radar-based Dataset Development for Human Activity Recognition

机译:基于雷达的人类活动识别的数据集发展

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Human activity recognition (HAR) is an important research problem and considerable efforts have been made in the past two decades to develop successful solutions. Datasets developed for HAR serve as a baseline for evaluating new HAR algorithms and play a pivotal role in advancing the research efforts in this domain. Hundreds of datasets have been developed by various researchers which focus on different types of motions and activities [1]. In this context, most of the efforts have been invested in developing the datasets which contain either the video or clips of 2D images of different types of motions. Due to the advent of 3D sensors, modern datasets also contain the information of the motion as well as the depth [2].
机译:人类活动识别(HAR)是一个重要的研究问题,在过去二十年中取得了相当大的努力来开发成功的解决方案。为Har开发的数据集用作评估新的HAR算法的基线,并在推进该领域的研究工作方面发挥关键作用。已经由各种研究人员开发了数百个数据集,这些研究人员专注于不同类型的运动和活动[1]。在这种情况下,大多数努力已经投入开发包含不同类型运动的2D图像的视频或剪辑的数据集。由于3D传感器的出现,现代数据集还包含动作的信息以及深度[2]。

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