Abstract
Studies have shown that children can be exposed to smart devices at a very early age. This has important implications on research in children-computer interaction, children online safety and early education. Many systems have been built based on such research. In this work, we present multiple techniques to automatically detect the presence of a child on a smart device, which could be used as the first step on such systems. Our methods distinguish children from adults based on behavioral differences while operating a touch-enabled modern computing device. Behavioral differences are extracted from data recorded by the touchscreen and built-in sensors. To evaluate the effectiveness of the proposed methods, a new data set has been created from 50 children and adults who interacted with off-the-shelf applications on smart phones. Results show that it is possible to achieve 99% accuracy and less than 0.5% error rate after 8 consecutive touch gestures using only touch information or 5 seconds of sensor reading. If information is used from multiple sensors, then only after 3 gestures, similar performance could be achieved.
Abstract (translated)
研究表明，儿童在很小的时候就可以接触到智能设备。这对儿童 - 计算机互动，儿童在线安全和早期教育的研究具有重要意义。基于这样的研究已经建立了许多系统。在这项工作中，我们提出了多种技术来自动检测智能设备上是否存在儿童，这可以作为此类系统的第一步。我们的方法在操作支持触摸的现代计算设备时基于行为差异将儿童与成人区分开来。从触摸屏和内置传感器记录的数据中提取行为差异。为了评估所提方法的有效性，已经从50名儿童和成人中创建了一个新的数据集，他们与智能手机上的现成应用程序进行交互。结果表明，在仅使用触摸信息或5秒的传感器读数的连续8次触摸手势之后，可以实现99％的准确度和小于0.5％的错误率。如果从多个传感器使用信息，则仅在3次手势之后，可以实现类似的性能。
URL
https://arxiv.org/abs/1808.01680
