论文标题
SuperPower Glass:在可穿戴系统中提供不引人注目的实时社交线索
Superpower Glass: Delivering Unobtrusive Real-time Social Cues in Wearable Systems
论文作者
论文摘要
我们已经开发了一种用于自动面部表情识别的系统,该系统在Google Glass上运行,并为佩戴者提供实时社交线索。我们将系统评估为自闭症谱系障碍儿童(ASD)的行为辅助,他们可以从实时的非侵入性情绪提示中受益匪浅,并且比神经型发育的儿童对感觉输入更敏感。此外,我们提出了一个移动应用程序,该应用程序使可穿戴援助的用户可以在视频播放栏上查看其视频以及自动策划的情感信息。这将我们的学习援助纳入行为疗法的背景。为了扩展我们以前描述LAB试验的工作,本文深入介绍了我们的系统和应用程序级设计决策,以及在使用ASD的多个儿童使用ASD在本地迭代试验中收集的界面学习。
We have developed a system for automatic facial expression recognition, which runs on Google Glass and delivers real-time social cues to the wearer. We evaluate the system as a behavioral aid for children with Autism Spectrum Disorder (ASD), who can greatly benefit from real-time non-invasive emotional cues and are more sensitive to sensory input than neurotypically developing children. In addition, we present a mobile application that enables users of the wearable aid to review their videos along with auto-curated emotional information on the video playback bar. This integrates our learning aid into the context of behavioral therapy. Expanding on our previous work describing in-lab trials, this paper presents our system and application-level design decisions in depth as well as the interface learnings gathered during the use of the system by multiple children with ASD in an at-home iterative trial.