面向智慧家庭的虚拟体验系统的研究与开发

针对传统室内设计在用户体验方面缺少沉浸感、交互性等问题,提出了一种基于虚拟现实技术的家居互动设计虚拟体验系统的实现方法,本方法围绕虚拟现实的基本特征,使用三维软件制作虚拟场景,使用Unity游戏引擎和基于物理渲染技术提高虚拟场景的逼真度,使用虚拟现实设备HTCVive为用户提供交互体验操作。通过虚拟体验系统的开发,提出了一种新的室内家居设计体验方法。     

自然的三维场景视点控制系统

为了增强三维场景视点控制的自然性,给用户更多的交互沉浸感,设计并实现了一套自然的三维场景视点控制系统.系统采用立体视觉方法定位用户头部的三维空间运动,并利用计算机图形学原理将头部运动映射为三维场景的视点控制.同时,为了方便用户锁定当前视点,系统采用语音识别方法实现基于头部运动的视点控制方式的启动和关闭.测试实验结果表明,该系统是可行的、实用的.     

基于触觉交互界面的虚拟现实警务训练系统

虚拟现实凭借着其高沉浸感的体验,在警务仿真培训中有着广泛应用,由于商用虚拟现实系统多关注视觉反馈,难以使用标准的手控器为警务培训提供逼真的触觉交互体验。触觉交互界面基于多功能的离散单点触控交互系统,可实现虚拟现实中的道具操作直接交互,针对虚拟训练中的警务场景,该系统能够识别用户所选道具,并响应用户的交互动作,以提高虚拟现实系统的交互真实性。该系统使用HTC Vive 追踪器对用户进行运动捕捉,以生成人体骨架驱动虚拟代理。同时,使用单片机获取并处理用户的道具选择信息及用户与道具的交互信息,再通过蓝牙通信传输至上位机。硬件设计采用 STM32F103 系列中的 C8T6 最小系统板,相关功能通过软件 Keil5 编程实现。实验验证了系统的正确性和可行性,能够提供多样的物理触觉代理,增强了虚拟环境中的交互体验。该系统为虚拟现实交互技术提供了新的思路和方向,具有很好的应用前景。     

智能手机动效设计研究

智能手机上,动效无处不在,是手机操作过程中呈现和使用频率最高的功能之一.针对智能手机动效设计的基本原则、方法和准则展开研究,就动效设计的体验价值和商业价值,围绕人与智能手机之间的自然交互问题进行了综合探讨.通过智能手机经典动效交互的案例研究,分析了多场景下的人机自然交互的动效设计体验,探讨了基于用户对智能手机动效设计的需求来建立相应的人机自然交互系统的理论与方法.在实际中的应用表明,所提出的动效设计准则便于交互、信息准确、用户友好.     

基于界面交互设计的情感体验设计研究

数字时代,多媒体交互产品充斥在我们生活的方方面面,用户不再是被动的工具使用者,他们越来越重视自身与交互产品的感知程度,开始关注自身的情感体验,寻求交互与自身的情感关联。以用户体验为中心的交互设计从用户情感体验出发,在视觉系统和交互行为中不断深入研究和探索对未来交互领域的发展,这具有极为重要的价值和意义。     

面向智能家居系统的主动交互设计研究

随着物联网和人工智能在智能家居领域的应用,智能家居具备了主动交互能力.针对智能家居主动交互平衡信息传递和用户体验的问题,提出面向智能家居系统主动交互设计策略.首先,通过文献研究总结了智能家居系统主动交互的发展现状,将其总结为3个特征,即交互策略逐步采用自适应场景模式、交互通道逐步转向多模态和交互程度逐步呈现低打扰度,为策略设计提供了理论支撑;其次,梳理出智能家居场景要素和不同交互模态打扰度等级,并提出了在不同场景的任务下智能家居对应的主动交互策略;最后,采用“绿野仙踪”方法在自行搭建的实验场景下进行实验,并以SUS量表和USE问卷作为评价指标,验证了所提策略的可用性和满意度.此外,构建了智能家居不同场景与主动交互打扰度的对应关系,以期为后续研究提供参考.     

具有协同交流功能的虚拟物理实验室

为解决虚拟实验中师生不能有效交流的问题,采用VRML-JS-Java通信机制实现了一种具有交流功能的虚拟物理实验室.介绍了实验室总体设计和场景层次结构,阐述了三维场景的建模过程和流程,重点对交互功能的服务器端、客户端、用户间的交互与感知,以及VRML虚拟场景与Java接口等关键技术进行实现.经过发布与测试,表明虚拟物理实验室具有良好的层次性、可重用性和互操作性,在大学实验教学改革中具有较高的实用价值.     

基于Virtools的虚拟校园在线交互设计与实现

在虚拟校园中,人性化的人机交互设计可提高系统的可用性和用户友好性。本系统在线展示了校园的仿真模型,并提供了可供用户操作的虚拟人物及其交互功能,使用户能尽可能真实地了解校园。为了使用户在浏览虚拟校园时获得更好的在线交互体验,提出并实现了虚拟校园系统需要解决的几个主要交互功能:人物及其视角交互、场景链接交互、信息链接交互、信息提示交互以及虚拟场景中物体的交互。该系统采用了多场景建模方法,以大化小、分而治之,避免使用过大的场景,缩短了系统的在线响应时间;使用Virtools自带的VSL脚本语言实现系统较复杂的交互功能,提高了程序的可重用性和可维护性,同时减少了系统占用的内存空间,提高了运行速度,并且实现了一些Virtools内置的BB不能实现的功能。     

虚拟手术中血流特效场景仿真的研究

血流特效场景可以增强虚拟手术的真实感。虚拟手术中的血流特效场景包括了有交互的血液模拟及血管壁模拟。首先基于光滑粒子流体动力学,使用Physx物理引擎模拟血液流动的物理形态,并利用Screen Space Flow算法对血流表面进行实时渲染。然后基于质点-弹簧模型,提出使用Physx物理引擎模拟可交互、有弹性形变及可切割的血管壁。最后实现两个实验场景:场景一实现肺动脉内大规模血液流动的特效;场景二实现在用户交互下的血管壁形变和切割,并通过触发事件实现血管壁破裂流血的特效。实验结果表明,该血流及血管壁模拟方法在40 000个粒子下仍能保证实时绘制,满足虚拟手术的需求。     

手机产品交互设计与用户体验探析

运用交互设计和用户体验的基本概念、产品交互系统组成图解、用户体验四元素,结合手机产品设计的用户调查和列表分析,获得了手机产品交互设计和用户体验的最终评价,通过这一比较和探析的过程证明,交互设计是未来设计尤其是工业产品设计的努力的方向和目标,用户体验是设计的终极参照。     

Understanding and designing for intermediated information tasks in India

It's important to consider both primary and secondary users when designing for intermediated interaction scenarios in India and elsewhere in the developing world. However, most of this research has focused on supporting users in the developed world who are voluntarily collaborating on a computing task. Many users in India, especially those from disadvantaged classes, have only partial or no physical access to computing devices. We refer to these users as secondary users to distinguish them from the primary users that the interface design process traditionally considers. Secondary users must interact with information resources via a proxy primary user who has the required access rights and skills. The proxy's filtering and funneling decisions limit the secondary users' information-seeking behavior; the secondary user might also have an unequal power relationship with the proxy. Therefore, secondary users might never know the full scope of actions and knowledge available to them. If we are to realize the egalitarian potential of computing, we must consider secondary users in the design process. We must develop technologies that recognize the needs and aspirations of all classes of users, including those without direct access to the user interface. In fact, by designing user interfaces explicitly supporting intermediated tasks, both primary and secondary users can benefit.     

The scenario‐based usability checklist development for home appliance design: A case study

In the past decade, home appliances have been rapidly developed to satisfy the various requirements of users. Thus, there are increases in requirements to explore appropriate evaluation methods that reflect the usability of home appliances quickly and comprehensively. This study aims to develop a scenario‐based usability checklist for product designers early in the design process. In this study, the scenario‐based usability checklist consists of two parts: 1) a heuristic evaluation checklist, and 2) a scenario evaluation checklist. In heuristic evaluation checklist development, usability factors of home appliances are extracted and then coupled to user interface (UI) elements. In scenario evaluation checklist development, scenarios are developed through brainstorming by focus group interview (FGI), and then evaluation elements are extracted from previous scenarios analysis. The proposed scenario‐based usability checklists can enable designers to evaluate product design quickly and comprehensively early in the development process with users' viewpoints. © 2010 Wiley Periodicals, Inc.     

Interaction Unit Analysis: A New Interaction Design Framework

ABSTRACT

A pragmatic approach to interaction modeling is presented by which a designer can describe how the user gets tasks done with a newly developing system. The notation proposed allows an interaction designer to make explicit both how user actions cause visible or noticeable changes in the state of the machine and how the user is expected to use this feedback to generate the next action. Interaction Unit (IU) scenarios are constructed where each IU specifies one step in the cycle of interaction. Each IU specifies the visible system state that leads the user to take some action. In addition, the IU makes explicit the state of the goal stack at the start and end of the unit and the mental processes (recall, recognition, or affordance) required. In this way one can describe the intimate connection between goal, action, and the environment in user–machine interaction.

To demonstrate the completeness of IU scenario analysis, IU models are presented for some well-known problems in interaction design: hidden and partially hidden modes leading to unexpected system effects, insufficient cues for subgoal construction, insufficient cues for subgoal elimination, and inappropriate affordances for action. These scenarios are accompanied by procedures that designers can use to detect similar problems in putative interaction designs.

To demonstrate the feasibility of using IU scenario analysis in design, 4 graduate students were taught to use IU scenario analysis in a 3-hr session. They then worked as a group to evaluate a prototype handheld warehouse application. A comparable group was taught and then applied Cognitive Walkthrough. Both groups successfully completed the task and detected several problems rated as being of high severity by the designers of the prototype. Analysis of the problems detected by each group suggests that the two techniques are complimentary. IU scenario analysis may be most cost-effective for devices using new interaction paradigms, whereas Cognitive Walkthrough may be most cost-effective for designs using established interaction paradigms.     

基于普通纸笔的投影交互方法研究

投影交互使交互空间不再局限于屏幕,与其他方式相比具有更好的用眼舒适度,能够实现丰富 的交互效果,而笔式书写交互则有着与生俱来的自然性和高效性。结合二者优点,提出了一种基于普通纸笔的 投影交互方法,通过普通纸笔与计算机进行交互,摄像头用于采集手写内容,投影仪则用于识别效果呈现。另 外,通过卷积神经网络(CNN)和 KNN 结合使系统可自动适应用户的手写风格,提高了针对不同用户的手写体 识别率。在此基础上,针对教育领域设计了单词拼写和算式计算 2 个典型应用。经实验和用户调查,该交互方 法与其他交互方法相比,更舒适自然,具有较强的实用性。     

Eye movements as indices for the utility of life-like interface agents: A pilot study

We motivate an approach to evaluating the utility of life-like interface agents that is based on human eye movements rather than questionnaires. An eye tracker is employed to obtain quantitative evidence of a user’s focus of attention without distracting from the primary task. The salient feature of our evaluation strategy is that it allows us to measure important properties of a user’s interaction experience on a moment-by-moment basis in addition to a cumulative (spatial) analysis of the user’s areas of interest. We describe a pilot study in which we compare attending behavior of subjects watching the presentation of a computer-generated apartment layout and visualization augmented by three types of media: an animated agent, a text box, and speech only. The investigation of eye movements revealed that deictic gestures performed by the agent are more effective in directing the attentional focus of subjects to relevant interface objects than the media used in the two control conditions, at a slight cost of distracting the user from visual inspection of the object of reference. The results also demonstrate that the presence of an interface agent seemingly triggers natural and social interaction protocols of human users.     

Multimodal extraction of events and of information about the recording activity in user generated videos

In this work we propose methods that exploit context sensor data modalities for the task of detecting interesting events and extracting high-level contextual information about the recording activity in user generated videos. Indeed, most camera-enabled electronic devices contain various auxiliary sensors such as accelerometers, compasses, GPS receivers, etc. Data captured by these sensors during the media acquisition have already been used to limit camera degradations such as shake and also to provide some basic tagging information such as the location. However, exploiting the sensor-recordings modality for subsequent higher-level information extraction such as interesting events has been a subject of rather limited research, further constrained to specialized acquisition setups. In this work, we show how these sensor modalities allow inferring information (camera movements, content degradations) about each individual video recording. In addition, we consider a multi-camera scenario, where multiple user generated recordings of a common scene (e.g., music concerts) are available. For this kind of scenarios we jointly analyze these multiple video recordings and their associated sensor modalities in order to extract higher-level semantics of the recorded media: based on the orientation of cameras we identify the region of interest of the recorded scene, by exploiting correlation in the motion of different cameras we detect generic interesting events and estimate their relative position. Furthermore, by analyzing also the audio content captured by multiple users we detect more specific interesting events. We show that the proposed multimodal analysis methods perform well on various recordings obtained in real live music performances.     

Methodological issues in product evaluation: the influence of testing environment and task scenario

This article examines the utility of two commonly used approaches in the evaluation of interactive consumer products: lab-based testing and single task scenarios. These are compared to two more complex and resource-demanding approaches (field-based testing and dual task scenarios) with regard to the test results they produce. An experiment with N = 80 users was carried out, employing a 2 (laboratory vs. field) by 2 (single task vs. dual task scenario) by 2 (on-product information: present vs. absent) between-subjects design. On-product information (advising users to save water and electricity during kettle usage) represented the intervention, of which the effects on user behaviour were compared under the different experimental conditions. The main finding was that the impact of on-product information on user behaviour was strongest in the lab-based testing environment using a single task scenario (i.e., most economical testing condition), compared to the three other experimental conditions. The work found similar effects for self-report measures. The findings of the study point to the risk that the effects of system redesign on user behaviour may be overestimated if low-fidelity testing approaches are employed. The relevance of these findings for other application areas is also discussed (e.g., design of warnings).     

In-Vehicle Information Systems to Meet the Needs of Drivers

In-Vehicle Information Systems (IVISs) integrate most of the secondary functions available within vehicles. These secondary functions are aimed at enhancing the driving experience. To successfully design and evaluate the performance of these systems, a thorough understanding of the task, user, and system is required. This article presents a review of these three variables in the context of IVISs, which aims to enhance understanding of this specific task–user–system interaction. A framework for modeling system performance for the task–user–system interaction is also proposed. This will allow designers and evaluators of IVISs to make predictions about system performance and to design systems that meet a set of criteria for usable IVISs.     

Exploiting behavioral user models for point of interest recommendation in smart museums

ABSTRACT

The Internet of Things (IoT) holds the promise to blend real-world and online behaviors in principled ways, yet we are only beginning to understand how to effectively exploit insights from the online realm into effective applications in smart environments. Such smart environments aim to provide an improved, personalized experience based on the trail of user interactions with smart devices, but how does recommendation in smart environments differ from the usual online recommender systems? And can we exploit similarities to truly blend behavior in both realms to address the fundamental cold-start problem? In this article, we experiment with behavioral user models based on interactions with smart devices in a museum, and investigate the personalized recommendation of what to see after visiting an initial set of Point of Interests (POIs), a key problem in personalizing museum visits or tour guides, and focus on a critical one-shot POI recommendation task—where to go next? We have logged users' onsite physical information interactions during visits in an IoT-augmented museum exhibition at scale. Furthermore, we have collected an even larger set of search logs of the online museum collection. Users in both sets are unconnected, for privacy reasons we do not have shared IDs. We study the similarities between users' online digital and onsite physical information interaction behaviors, and build new behavioral user models based on the information interaction behaviors in (i) the physical exhibition space, (ii) the online collection, or (iii) both. Specifically, we propose a deep neural multilayer perceptron (MLP) based on explicitly given users' contextual information, and set-based extracted features using users' physical information interaction behaviors and similar users' digital information interaction behaviors. Our experimental results indicate that the proposed behavioral user modeling approach, using both physical and online user information interaction behaviors, improves the onsite POI recommendation baselines' performances on all evaluation metrics. Our proposed MLP approach achieves 83% precision at rank 1 on the critical one-shot POI recommendation problem, realizing the high accuracy needed for fruitful deployment in practical situations. Furthermore, the MLP model is less sensitive to amount of real-world interactions in terms of the seen POIs set-size, by backing of to the online data, hence helps address the cold start problem in recommendation. Our general conclusion is that it is possible to fruitfully combine information interactions in the online and physical world for effective recommendation in smart environments.     

面向5G车联网场景的移动任务动态卸载策略研究

由于车辆自身的高速移动性和资源有限性等特征,使得采用传统通信和计算手段的车联网场景无法满足用户日益增长的数据计算需求和体验质量需求。采用5G和边缘计算技术构建的新型车联网架构可以满足以上需求,但由于网络结构的变化,需设计适合新场景下的车辆任务通信和计算策略。针对5G车联网场景下的移动车辆任务动态卸载问题进行研究,提出了对应的动态任务分配策略和卸载调度低时延算法。车辆会根据提出的策略和算法将未完成的计算任务卸载到相应的 MEC 服务器或车辆上,并且计算结果将通过边缘服务器之间的联合通信或直接从被选择接受卸载任务的附近空闲车辆上直接返回给车主。仿真结果表明,所提出的策略和算法在优化卸载延迟方面具有良好的性能,并提高了用户体验质量。