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行为影像学与自闭症研究

Behavior Imaging and the Study of Autism
课程网址: http://videolectures.net/uai2011_rehg_behavior/  
主讲教师: James M. Rehg
开课单位: 乔治亚理工学院
开课时间: 2011-08-26
课程语种: 英语
中文简介:

从婴儿期开始,个人就掌握了对健康和多产的生活至关重要的社交和沟通技巧。发育迟缓的儿童在获得这些技能方面面临巨大挑战,从而导致巨大的终生风险。自闭症谱系障碍(ASD)的儿童代表着特别重要的风险类别,这是由于ASD的诊断率及其后果增加。由于尚不清楚ASD的遗传基础,因此对该疾病的诊断,治疗和研究从根本上取决于对行为的观察。不幸的是,当前用于获取和分析行为数据的方法非常费力,以至于无法大规模应用。在本演讲中,我将描述我们在“行为影像”中的研究议程,该研究议程的目标是捕获,建模和分析儿童及其照顾者和同伴之间的社交和交流行为。我们正在开发用于分析视觉,音频和可穿戴传感器数据的计算方法和统计模型。我们的目标是为大规模收集和解释行为数据开发一套新的功能。我将描述该领域出现的一些统计建模方面的研究挑战,并在基于视频的社交互动分析中展示说明性的结果。

课程简介: Beginning in infancy, individuals acquire the social and communication skills that are vital for a healthy and productive life. Children with developmental delays face great challenges in acquiring these skills, resulting in substantial lifetime risks. Children with an Autism Spectrum Disorder (ASD) represent a particularly significant risk category, due both to the increasing rate of diagnosis of ASD and its consequences. Since the genetic basis for ASD is unclear, the diagnosis, treatment, and study of the disorder depends fundamentally on the observation of behavior. Unfortunately, current methods for acquiring and analyzing behavioral data are so labor-intensive as to preclude their large scale application. In this talk, I will describe our research agenda in Behavior Imaging, which targets the capture, modeling, and analysis of social and communicative behaviors between children and their caregivers and peers. We are developing computational methods and statistical models for the analysis of vision, audio, and wearable sensor data. Our goal is to develop a new set of capabilities for the large-scale collection and interpretation of behavioral data. I will describe several research challenges in statistical modeling which arise in this area, and present illustrative results in the video-based analysis of social interactions.
关 键 词: 传感器数据; 统计建模
课程来源: 视频讲座网
数据采集: 2021-04-21:zyk
最后编审: 2021-04-21:zyk
阅读次数: 42