IDInteraction: Capturing Indicative Usage Models in Software for Implicit Device Interaction

IDInteraction：捕获软件中用于隐式设备交互的指示性使用模型

• 批准号: EP/M017133/1
• 负责人: Caroline Jay
• 金额: $ 13.67万
• 依托单位: University of Manchester
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2015
• 资助国家: 英国
• 起止时间: 2015 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FM017133%2F1
• 关键词: IDInteraction; Capturing; Indicative; Usage; Models

The IDInteraction project asks: can we exploit models of human behaviour to move away from direct, unambiguous user commands, towards seamless user-device interaction? It will investigate and develop the techniques to capture 'Indicative Usage Models (IUMs), behavioural patterns or cues that precede a particular activity, and translate these into software-based 'Indicative Usage Patterns' (IUPs), to drive interaction with an app. The project will focus on future television broadcasting, examining the extent to which it is possible to capture IUMs from device sensor and event data, and deploy these as IUPs to pull content (additional information or related activities) to a 'second screen companion app', which a viewer watches on a mobile device alongside a TV programme.The core of the research - investigating the extent to which we can anticipate user commands and requests - will play an important role in shaping the way we use future technology. The Internet of Things is fast becoming a reality, but the appropriate paradigms for interacting with it are far from understood. A rapidly growing number of connected devices means a potentially vast increase in the types of technology which people must use successfully. Whilst a person may be prepared to learn how to use a new home automation system or car, expecting him or her to do this for every machine with which there is a cursory encounter is unrealistic. We have already started to understand that interactive experiences which take fundamental human perception and thought processes into account are more successful than those which require significant learning on the part of the user. Implicit Device Interaction, where devices automatically know what the user wants, before a command is issued, is the next step.The scenario investigated - second screen viewing - is also particularly timely. Broadcasters are keen to exploit the creative potential of a context where people are watching television with a mobile device, not least because it is set to become the principle form of TV viewing in the next few years. At present, however, the scenario is not well understood: whilst some research has focused on social aspects of this situation, very little has examined the perceptual or behavioural aspects of second screen interaction. Current companion apps, designed to complement the main programme, push information to the mobile device at given points in time, and this change on the secondary screen, which occurs in peripheral vision, is potentially distracting. A situation where information flow intuitively stops and starts according to the location of the viewer's attention is a highly desirable goal.IDInteraction is an ambitious research project, investigating an aspect of human behaviour that is crucial to the future development of implicit user interfaces, and has been planned to tackle the problem from end-to-end. By studying a slice of the research problem, from modelling behaviour to testing a new user interface, it will provide an overview of the theoretical and technical challenges that the development of seamless user-device interaction will entail, and flag key areas for further investigation. From the perspective of effective software development, the project entails a considerable degree of risk: IUMs may be difficult to capture and deploy, and seamless information provision may be challenging to implement in this context. From the perspective of building theory in this area, such results would still have significant value, however. Improving our understanding of the limits of implicit interaction is crucial to moving this important, emergent, field forward.

IDInteraction项目要求：我们能否利用人类行为模型，从直接、明确的用户命令转向无缝的用户-设备交互？它将研究和开发捕获“指示性使用模型（IUM）”、特定活动之前的行为模式或线索的技术，并将其转换为基于软件的“指示性使用模式”（IUP），以驱动与应用程序的交互。该项目将重点关注未来的电视广播，检查从设备传感器和事件数据捕获IUM的可能性程度，并将其部署为IUP，将内容（附加信息或相关活动）拉到“第二屏幕伴侣应用程序”，观众可以在移动终端上观看电视节目。研究的核心--调查我们能在多大程度上预测用户命令和请求--将在塑造我们使用未来技术的方式方面发挥重要作用。物联网正在迅速成为现实，但与之交互的适当范例还远未被理解。连接设备数量的快速增长意味着人们必须成功使用的技术类型可能会大幅增加。虽然一个人可能准备学习如何使用新的家庭自动化系统或汽车，但期望他或她对粗略遇到的每台机器都这样做是不现实的。我们已经开始认识到，考虑到人类基本感知和思维过程的交互式体验比那些需要用户大量学习的体验更成功。下一步是隐式设备交互，即设备在发出命令之前自动知道用户想要什么。所研究的场景-第二屏幕查看-也特别及时。广播公司热衷于利用人们用移动终端看电视的背景下的创造潜力，尤其是因为它将在未来几年成为电视观看的主要形式。然而，目前，这种情况还没有得到很好的理解：虽然一些研究集中在这种情况下的社会方面，但很少有研究第二屏幕交互的感知或行为方面。目前的配套应用程序旨在补充主程序，在给定的时间点向移动终端推送信息，而副屏幕上的这种变化发生在周边视觉中，可能会分散注意力。信息流直观地停止和开始根据观众的注意力的位置的情况是一个非常理想的目标。IDInteraction是一个雄心勃勃的研究项目，调查人类行为的一个方面，这是至关重要的隐式用户界面的未来发展，并已计划从端到端解决问题。通过研究一部分研究问题，从建模行为到测试新的用户界面，它将概述无缝用户设备交互的发展将带来的理论和技术挑战，并标记进一步调查的关键领域。从有效软件开发的角度来看，该项目具有相当大的风险：综合统一管理系统可能难以获取和部署，在这种情况下，无缝提供信息可能难以实现。然而，从这一领域的建筑理论的角度来看，这样的结果仍然具有重要的价值。提高我们对内隐互动的局限性的理解，对于推动这一重要的、新兴的领域向前发展至关重要。

项目成果

Contrasting delivery modes for second screen TV content-Push or pull?

第二屏幕电视内容的对比交付模式——推还是拉？

• DOI: 10.1016/j.ijhcs.2019.03.007
• 发表时间: 2019
• 期刊: International Journal of Human-Computer Studies
• 影响因子: 5.4
• 作者: Brown A

Digital Scholarship and Open Science in Psychology and the Behavioral Sciences (Dagstuhl Perspectives Workshop 15302)

心理学和行为科学中的数字学术和开放科学（Dagstuhl Perspectives Workshop 15302）

• DOI: 10.4230/dagrep.5.7.42
• 发表时间: 2016
• 期刊: Dagstuhl Reports (DagRep)
• 作者: Garcia Castro A