论文成果 / Publications
2019
Facilitating Temporal Synchronous Target Selection through User Behavior Modeling
Abstract
Temporal synchronous target selection is an association-free selection technique: users select a target by generating signals (e.g., finger taps and hand claps) in sync with its unique temporal pattern. However, classical pattern set design and input recognition algorithm of such techniques did not leverage users’ behavioral information, which limits their robustness to imprecise inputs. In this paper, we improve these two key components by modeling users’ interaction behavior. We generated pattern sets for up to 22 targets that minimized the possibility of confusion due to imprecise inputs, validated that the optimized pattern sets could reduce error rate from 23% to 7% for the classical Correlation recognizer. We also tested a novel Bayesian, which achieved higher selection accuracy than the Correlation recognizer when the input sequence is short.
AR Assistive System in Domestic EnvironmentUsing HMDs: Comparing Visualand Aural Instructions
Abstract
Household appliances are becoming more varied. In daily life, people usually refer to printed documents while they learn to use different devices. However, augmented reality (AR) assistive systems providing visual and aural instructions have been proposed as an alternative solution. In this work, we evaluated users’ performance of instruction understanding in four different ways: (1) Baseline paper instructions, (2) Visual instructions based on head mounted displays (HMDs), (3) Visual instructions based on computer monitor, (4) Aural instructions. In a Wizard of Oz study, we found that, for the task of making espresso coffee, the helpfulness of visual and aural instructions depends on task complexity. Providing visual instructions is a better way of showing operation details, while aural instructions are suitable for presenting intention of operation. With the same visual instructions on displays, due to the limitation of hardware, the HMD-users complete the task in the longest duration and bear the heaviest perceived cognitive load.
2018
Tap-to-Pair: Associating Wireless Devices with Synchronous Tapping
Abstract
Tap-to-Pair is a spontaneous device association technique that initiates pairing from advertising devices without hardware or firmware modifications. Tapping an area near the advertising device's antenna can change its signal strength. Users can then associate two devices by synchronizing taps on the advertising device with the blinking pattern displayed by the scanning device. By leveraging the wireless transceiver for sensing, Tap-to-Pair does not require additional resources from advertising devices and needs only a binary display (e.g. LED) on scanning devices.
HeadGesture: Hands-Free Input Approach Leveraging Head Movements for HMD Devices
Abstract
We propose HeadGesture, a hands-free input approach to interact with HMD devices. Using HeadGesture, users do not need to raise their arms to perform gestures or operate remote controllers in the air. Instead, they perform simple gestures with head movement to interact. In this way, users' hands are free to perform other tasks and it reduces the hand occlusion of the field of view and alleviates arm fatigue. Evaluation results demonstrate that the performance of HeadGesture is comparable to mid-air hand gestures and users feel significantly less fatigue.
Lip-Interact: Improving Mobile Device Interaction with Silent Speech Commands
Abstract
We present Lip-Interact, an interaction technique that allows users to issue commands on their smartphone through silent speech. Lip-Interact repurposes the front camera to capture the user's mouth movements and recognize the issued commands with an end-to-end deep learning model. Our system supports 44 commands for accessing both system-level functionalities (launching apps, changing system settings, and handling pop-up windows) and application-level functionalities (integrated operations for two apps). We verify the feasibility of Lip-Interact with three user experiments: evaluating the recognition accuracy, comparing with touch on input efficiency, and comparing with voiced commands with regards to personal privacy and social norms. We demonstrate that Lip-Interact can help users access functionality efficiently in one step, enable one-handed input when the other hand is occupied, and assist touch to make interactions more fluent.
CCCF 2018|横看成岭侧成峰
Abstract
CCCF第 100期时我还是在任的副主编和专题主编,那时虽很兴奋,但有限的精力只能忙于及时出好刊,来不及说"题外话";每年12期的迅速迭代,CCCF 就要迎来她的第150期了,仍是匆匆忙忙中,还是要说一说我曾付诸60多期心血的CCCF专题。
2004年,中国计算机学会终于改革成为一个以个人会员为基础的学会,活动越来越多,会员发展快、参与度高,在这种情势下,李国杰老师明确指出∶学会要姓"学",要做好学术活动,搞出学术产品。因此,出刊成为学会的一项重要任务,这本定位于面向读者、面向全体会员的学会通讯,应运而生(李老师作为理事长,主动担当了主编重任),至今,影响力越来越大。
正如李老师在创刊号上指出的,CCCF作为学会的会刊,要多发表有深度和可读性的文章,揭示计算机学科方向发展的"深刻动因",要多发表激发想象力的好文章,"成为激励自主创新的号角"。而专题,从发刊起,就占据着CCCF的封面(事实上,专题最初就叫做"封面报道"),不仅文章总体篇幅占比大,而且主题突出,是当然的"重头",办好的责任当然也重大。2012年初,我接过了聘书,也就接住了这份责任,一份紧绷的责任,并且,本来一年一聘的岗位,一年后是一聘两年,两年后又是两年,"意外"地为专题连续工作了五年。
CCCF 2018|自然人机交互
Abstract
人机交互是人与计算机之间为完成某项任务所进行的信息交换过程。计算机形态和使用情境(context)日益复杂多样,交互技术已经成为终端和应用创新的核心竞争力,自然交互是发展趋势。我们希望,人们与手持设备、家居设备、穿戴设备、机器人、无人车,在很多场景中以更自然的模态(比如用语音,用语义丰富的手势,甚至是我们日常的行为)发生互动,人们能获得可理解性与感受效果俱佳的信息反馈。所谓的自然,是在信息呈现和交互表达上,最大程度地符合人对现实世界已有的认知,信道充分,并能降低甚至无须学习成本,而在表达上,还体现在人不需要很精准的表达,可以是某种模糊的表达和传达的方式,而机器端能够给我们准确的理解和精准的服务。
CCCF2018|自然文本输入中的动作建模
Abstract
人机界面是人与计算机之间传递、交换信息的桥梁。几十年来,人机界面的发展越来越强调交互的自然性,即用户的交互行为与其生理和认知的习惯相吻合。人机交互的方式经历了命令行、图形用户界面、 触摸交互和三维空中交互的演变。其结果是,交互的自然性逐渐提高,但由于交互接口尺寸的限制和触觉等反馈信道受限,导致交互信号的精度和交互效率逐渐降低。这种自然性和高效性之间的制约关系,成为了人机交互研究中的难题,如何在两者之间取得兼顾和平衡,是具有重要理论价值和实践意义的研究问题。 文本输入是指人通过人机界面向计算机输入文本信息的过程,是最基本的人机交互任务之一。在日常生活中,历史最为悠久和广为接受的文本输入方式是利用键盘。传统的键盘包括物理键盘和较大尺寸的软键盘,用户经过一段时间的练习后,基本上可以实现无错的文本输入。然而,在可穿戴设备、虚拟 / 增强现实等新一 代自然交互场景中,用户往往面临着交互接口尺寸极小(智能手表)、缺乏触觉反馈(空中交互)等挑战, 这使得用户难以保证输入的准确性,输入信号的信噪比较低。此时,传统的纠错能力弱的文本输入技术的输入正确率显著下降,最终导致其无法完成文本输入任务,或者在输入过程中导致用户紧张疲劳,输入效率低,输入体验差。
TOAST: Ten-Finger Eyes-Free Typing on Touchable Surfaces
Abstract
Touch typing on flat surfaces (e.g. interactive tabletop) is challenging due to lack of tactile feedback and hand drifting. In this paper, we present TOAST, an eyes-free keyboard technique for enabling efficient touch typing on touch-sensitive surfaces.We first formalized the problem of keyboard parameter (e.g. location and size) estimation based on users’ typing data.