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Sensor-based user interface concepts for continuous, around-device and gestural interaction on mobile devices

机译:基于传感器的用户界面概念,用于在移动设备上进行连续,围绕设备和手势的交互

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摘要

A generally observable trend of the past 10 years is that the amount of sensors embedded in mobile devices such as smart phones and tablets is rising steadily. Arguably, the available sensors are mostly underutilized by existing mobile user interfaces. In this dissertation, we explore sensor-based user interface concepts for mobile devices with the goal of making better use of the available sensing capabilities on mobile devices as well as gaining insights on the types of sensor technologies that could be added to future mobile devices. We are particularly interested how novel sensor technologies could be used to implement novel and engaging mobile user interface concepts.ududWe explore three particular areas of interest for research into sensor-based user interface concepts for mobile devices: continuous interaction, around-device interaction and motion gestures.ududFor continuous interaction, we explore the use of dynamic state-space systems to implement user interfaces based on a constant sensor data stream. In particular, we examine zoom automation in tilt-based map scrolling interfaces. We show that although fully automatic zooming is desirable in certain situations, adding a manual override capability of the zoom level (Semi-Automatic Zooming) will increase the usability of such a system, as shown through a decrease in task completion times and improved user ratings of user study. The presented work on continuous interaction also highlights how the sensors embedded in current mobile devices can be used to support complex interaction tasks.ududWe go on to introduce the concept of Around-Device Interaction (ADI). By extending the interactive area of the mobile device to its entire surface and the physical volume surrounding it we aim to show how the expressivity and possibilities of mobile input can be improved this way. We derive a design space for ADI and evaluate three prototypes in this context. HoverFlow is a prototype allowing coarse hand gesture recognition around a mobile device using only a simple set of sensors. PalmSpace a prototype exploring the use of depth cameras on mobile devices to track the user's hands in direct manipulation interfaces through spatial gestures. Lastly, the iPhone Sandwich is a prototype supporting dual-sided pressure-sensitive multi-touch interaction. Through the results of user studies, we show that ADI can lead to improved usability for mobile user interfaces. Furthermore, the work on ADI contributes suggestions for the types of sensors could be incorporated in future mobile devices to expand the input capabilities of those devices.ududIn order to broaden the scope of uses for mobile accelerometer and gyroscope data, we conducted research on motion gesture recognition. With the aim of supporting practitioners and researchers in integrating motion gestures into their user interfaces at early development stages, we developed two motion gesture recognition algorithms, the $3 Gesture Recognizer and Protractor 3D that are easy to incorporate into existing projects, have good recognition rates and require a low amount of training data. To exemplify an application area for motion gestures, we present the results of a study on the feasibility and usability of gesture-based authentication.ududWith the goal of making it easier to connect meaningful functionality with gesture-based input, we developed Mayhem, a graphical end-user programming tool for users without prior programming skills. Mayhem can be used to for rapid prototyping of mobile gestural user interfaces. ududThe main contribution of this dissertation is the development of a number of novel user interface concepts for sensor-based interaction. They will help developers of mobile user interfaces make better use of the existing sensory capabilities of mobile devices. Furthermore, manufacturers of mobile device hardware obtain suggestions for the types of novel sensor technologies that are needed in order to expand the input capabilities of mobile devices. This allows the implementation of future mobile user interfaces with increased input capabilities, more expressiveness and improved usability.
机译:过去10年中通常可以观察到的趋势是,嵌入在智能手机和平板电脑等移动设备中的传感器数量正在稳步增长。可以说,现有的移动用户界面几乎没有充分利用可用的传感器。在本文中,我们探索了用于移动设备的基于传感器的用户界面概念,目的是更好地利用移动设备上的可用传感功能,并深入了解可以添加到未来移动设备中的传感器技术的类型。我们特别感兴趣的是如何使用新颖的传感器技术来实现新颖而引人入胜的移动用户界面概念。 ud ud我们探索了三个特定的研究领域,以研究基于移动设备的基于传感器的用户界面概念:持续交互,围绕设备交互和运动手势。 ud ud对于连续交互,我们探索使用动态状态空间系统基于恒定的传感器数据流来实现用户界面。特别是,我们研究了基于倾斜的地图滚动界面中的缩放自动化。我们显示,尽管在某些情况下需要全自动缩放,但是增加手动缩放级别的功能(半自动缩放)会增加此类系统的可用性,这可以通过减少任务完成时间和提高用户评分来显示用户研究。所呈现的关于连续交互的工作还强调了如何将当前移动设备中嵌入的传感器用于支持复杂的交互任务。 ud ud我们继续介绍设备周围交互(ADI)的概念。通过将移动设备的交互区域扩展到其整个表面及其周围的物理体积,我们旨在展示如何以这种方式改善移动输入的表达能力和可能性。我们得出了ADI的设计空间,并在此背景下评估了三个原型。 HoverFlow是一个原型,仅使用一组简单的传感器即可在移动设备周围识别粗略的手势。 PalmSpace的原型探索了如何在移动设备上使用深度摄像头,以通过空间手势在直接操作界面中跟踪用户的手。最后,iPhone Sandwich是支持双面压敏多点触摸交互的原型。通过用户研究的结果,我们表明ADI可以改善移动用户界面的可用性。此外,关于ADI的工作还提出了一些建议,建议将来的移动设备中可以合并传感器的类型,以扩展这些设备的输入功能。 ud ud为了扩大移动加速度计和陀螺仪数据的使用范围,我们进行了研究运动手势识别。为了支持从业者和研究人员在开发的早期阶段就将运动手势集成到其用户界面中,我们开发了两种运动手势识别算法:3美元的Gesture Recognizer和Protractor 3D,它们很容易集成到现有项目中,具有良好的识别率和需要少量的培训数据。为了举例说明运动手势的应用领域,我们提出了基于手势的身份验证的可行性和可用性的研究结果。 ud ud为了简化将有意义的功能与基于手势的输入连接的目标,我们开发了Mayhem ,这是一种图形化的最终用户编程工具,适用于没有事先编程技能的用户。 Mayhem可用于移动手势用户界面的快速原型制作。本文的主要贡献是为基于传感器的交互开发了许多新颖的用户界面概念。它们将帮助移动用户界面的开发人员更好地利用移动设备的现有感官功能。此外,移动设备硬件的制造商获得了有关扩展移动设备输入功能所需的新型传感器技术类型的建议。这样可以实现未来的移动用户界面,并具有增强的输入功能,更具表现力和更高的可用性。

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    Kratz Sven;

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