论文标题
在烹饪方案中，用于使用微小活动和宏观活动进行复杂活动识别的数据集
A dataset for complex activity recognition withmicro and macro activities in a cooking scenario
论文作者
论文摘要
复杂的活动识别可以受益于理解构成它们的步骤。但是，当前的数据集仅使用一个标签注释，这阻碍了这个方向的研究。在本文中，我们描述了一个新的数据集，用于基于传感器的活动识别，该数据集在烹饪方案中具有宏观和微观活动。同时测量的三个感应系统，即运动捕获系统，跟踪体内25点；两个智能手机加速度计，一个在臀部上，另一个在前臂上；每个手腕上有两个智能手表。该数据集标记为配方（宏观活动）和步骤（微型活动）。我们使用传统的活动识别管道总结了基线分类的结果。该数据集旨在轻松用于测试和开发活动识别方法。
Complex activity recognition can benefit from understanding the steps that compose them. Current datasets, however, are annotated with one label only, hindering research in this direction. In this paper, we describe a new dataset for sensor-based activity recognition featuring macro and micro activities in a cooking scenario. Three sensing systems measured simultaneously, namely a motion capture system, tracking 25 points on the body; two smartphone accelerometers, one on the hip and the other one on the forearm; and two smartwatches one on each wrist. The dataset is labeled for both the recipes (macro activities) and the steps (micro activities). We summarize the results of a baseline classification using traditional activity recognition pipelines. The dataset is designed to be easily used to test and develop activity recognition approaches.
