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为了有视觉障碍的人而建立一个以人为本的机器学习社会互动平台

Human-Centered Machine Learning in a Social Interaction Assistant for Individuals with Visual Impairments
课程网址: http://videolectures.net/nips09_chakraborty_hcm/  
主讲教师: Shayok Chakraborty
开课单位: 亚利桑那州立大学
开课时间: 2010-01-19
课程语种: 英语
中文简介:
在过去的几十年中,人们越来越关注无障碍性,因此设计和开发了多种辅助技术,帮助视觉障碍患者进行日常活动。这些设备大多集中在增强盲人或视力受损用户与物体和环境(如计算机显示器、个人数字助理、手机、道路交通或杂货店)的交互作用上。尽管这些努力对这些人的生活质量至关重要,但也有必要(迄今尚未认真考虑)丰富盲人与其他人之间的互动。非言语线索(包括韵律、物质环境要素、交际者的出现和身体运动)占社会交往中交流信息的65%以上[1]。然而,在美国,超过110万法律上失明的人(以及3700万人)对这种社会交往的基本特权经验有限。这些人在处理日常社会生活中的互动时,仍然面临着基本的挑战。本文所描述的工作是基于社会互动助手的设计和开发,旨在通过提供有关个人及其周围环境的实时信息,丰富盲人的社会互动经验。社会互动辅助设备的实现涉及到在可穿戴的实时平台上解决模式分析和机器智能中的几个挑战性问题,如人的识别/跟踪、头部/身体姿势估计、手势识别、表情识别等。在我们对27名失明或视力受损的患者进行的最初焦点小组研究中,确定了这些患者每天面临的8项重大挑战。这些问题中的每一个都提出了需要解决的独特的机器学习挑战。
课程简介: Over the last couple of decades, the increasing focus on accessibility has resulted in the design and development of several assistive technologies to aid people with visual impairments in their daily activities. Most of these devices have been centered on enhancing the interaction of a user who is blind or visually impaired with objects and environments, such as a computer monitor, personal digital assistant, cellphone, road traffic, or a grocery store. Although these efforts are very essential for the quality of life of these individuals, there is also a need (which has so far not been seriously considered) to enrich the interactions of individuals who are blind, with other individuals. Non-verbal cues (including prosody, elements of the physical environment, the appearance of communicators and physical movements) account for as much as 65% of the information communicated during social interactions [1]. However, more than 1.1 million individuals in the US who are legally blind (and 37 million worldwide) have a limited experience of this fundamental privilege of social interactions. These individuals continue to be faced with fundamental challenges in coping with everyday interactions in their social lives. The work described in this paper is based on the design and development of a Social Interaction Assistant that is intended to enrich the experience of social interactions for individuals who are blind, by providing real-time access to information about individuals and their surrounds. The realization of a Social Interaction Assistant device involves solving several challenging problems in pattern analysis and machine intelligence such as person recognition/tracking, head/body pose estimation, gesture recognition, expression recognition, etc on a wearable real-time platform. A list of eight significant daily challenges faced by these individuals was identified in our initial focus group studies conducted with 27 individuals who are blind or visually impaired. Each of these problems raises unique machine learning challenges that need to be addressed.
关 键 词: 可访问性; 非语言线索; 社会互动助理; 机器学习
课程来源: 视频讲座网
最后编审: 2020-06-01:wuyq
阅读次数: 35