面向沉浸式流场可视化的多视图数据管理方法

由于沉浸式环境下的三维交互方式对二维界面操作不够友好,使得依赖于二维列表界面的流场数据管理任务变得复杂且低效。为了实现沉浸式虚拟环境下对流场数据高效的组织和管理,增强用户对流场空间信息的理解,提出一种基于多视图结合交互的沉浸式流场可视化数据块管理方法。该方法构建了一个三维小视图用于提供场景概览,并通过“主视图交互+小视图辅助“”小视图交互+主视图反馈”等多种多视图组合交互方式完成对多块流场数据的管理交互操作。最后构建了一个基于手势的沉浸式流场可视化系统,定义多项交互任务,从学习时长、完成时间和用户反馈几个方面对比了多视图方法和传统交互方法差异。实验结果表明,相比于传统交互方法,多视图方法可以显著提高数据管理任务的效率。     

不同视觉反馈对笔倾斜输入性能的影响

针对笔倾斜输入过程中存在遮挡、视角错觉和缺乏反馈等问题,分析了视觉反馈的增加对笔倾斜输入性能的影响.首先结合笔倾斜的特点设计了图形全跟踪、图形部分跟踪、图形无跟踪、数字全跟踪、数字部分跟踪和数字无跟踪6种不同的笔倾斜视觉反馈;然后通过对比实验考察了经过视觉反馈后,在直接和间接设备上完成不同角间距的目标选择任务时笔倾斜输入的性能.实验结果表明,视觉反馈可以有效地提升目标选择的速度,而跟踪机制可以有效地提高目标选择的准确度;图形反馈的速度快于数字反馈;全跟踪反馈的错误率低于部分跟踪反馈;在直接设备上完成目标选择任务速度快,但在间接设备上完成目标选择任务的准确度更高.最后给出了笔倾斜输入和视觉反馈的使用原则和建议,对笔式界面中的笔倾斜交互和视觉反馈设计具有指导意义.     

基于感知反馈的UI界面数据可视化传递仿真

由于现有数据传递方法未考虑用户操作习惯,导致UI界面数据可视化传递满意度不高,因此研究基于感知反馈的UI界面数据可视化传递方法.UI界面数据可视化传递平台总体结构包括底层数据库、中间层数据访问层以及上层用户端三部分,底层数据库具备数据统一管理以及数据共享功能;通过中间层数据访问层为UI界面数据可视化提供有效、快速接口;上层用户端通过前台检测用户所输入数据以及所显示信息,选取Active X平台作为可视化UI界面上层用户端平台,采集用户需求以及用户感知数据,利用感知反馈方法获取用户操作习惯,通过感知反馈结果实现传递函数设计.仿真测试结果表明,将上述方法应用于UI界面数据可视化传递中,可获取较优的UI界面可视化渲染效果,且用户满意度高.     

分层卫星网络中的接入策略研究

研究了在分层分域卫星网络结构下的用户接入问题,包括网络节点编址、用户位置信息注册和更新、多星接入策略等,通过比较几种单层卫星网络常用的多星接入策略,提出了多层卫星网络的多星接入策略,最后对提出的接入策略在双层卫星网络上进行了仿真分析,得出了接入策略适用于分层卫星网络的结论。     

目标点击操作中不同方向对笔压性能影响的研究

在基于Fitts定理的目标点击任务中,不同的操作方向可能会对笔尖压力的使用性能产生影响,但Fitts定理却忽视了对方向因素的考察。因此,采用实证研究方法设计了两类方向,一类是矩形条菜单方向(北-南,西-东,东北-西南和东南-西北),另一类是压力增减方向(分别在4种方向的矩形条菜单上逐步增大压力(Pressure Increase)或逐步减小压力(Pressure Decrease)来选择两个目标,分别称之为PI Pointing和PD Pointing操作),考察了在基于Fitts定理的点击任务中不同方向对笔压使用性能的影响。实验要求12名实验者依次获取并选择矩形条上的两个不同间距和不同大小的目标。实验结果表明,不同的压力增减方向对笔压的使用性能有影响,而不同的矩形条菜单方向对笔压的使用性能没有显著性差异。本研究对基于笔压使用的用户交互界面设计具有帮助和指导作用。     

基于潜在狄利克雷分配的图像多层视觉表示方法

针对前馈型图像多层视觉表示方法难以处理局部模糊情况,提出一种基于潜在狄利克雷分配(LDA)的图像多层视觉表示方法——LDA-IMVR。通过递归的概率分解方式,获得LDA的递归生成模型;同时,通过学习和推断多层结构的所有分层,以及利用反馈方式来提高分类学习性能。在Caltech 101数据集上的实验结果表明,与相关的多层视觉表示方法比较,LDA-IMVR提高了数据对象的分类性能,并且在分量学习和图像特征区域可视化方面也得到了较好的效果。     

基于Yes/No反馈的视觉问答方法

针对视觉问答任务中问题语句可能存在的歧义,文中提出基于Yes/No反馈的视觉问答方法,通过Yes/No的反馈机制判断模型第一次得出答案的正误.当用户给出的反馈信息为No时,重新解析该问题,生成多种消歧后的问题,产生不同的候选答案,输出最高置信度的答案作为最终结果.在CLEVR、CLEVR-CoGenT基准数据集上的实验表明文中方法精度较高.     

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。     

手机三维菜单绩效预测模型

菜单是手机界面的重要交互部件,手机功能增加所带来的菜单规模增大与手机小屏幕形成日益突出的矛盾.三维界面技术可以提高界面信息容量,因此,在手机上引入三维菜单概念是一个值得研究的课题.相应地,需要解决手机三维菜单用户操作绩效的评估问题.模型预测评估法能使研究人员和设计人员快速和以较低成本对用户界面进行评估.因此,基于Fitts定律和Hick-Hyman定律,建立了预测评估手机三维菜单操作绩效的定量模型.通过实验检验了模型的有效性,并将其与相关模型进行了对比分析.实验结果表明,实验得到的数据与该模型预测数据吻合较好,并且与相关模型相比该模型预测数据与实验数据的相关度最高.     

悬浮空间中的触觉反馈在多对象选择任务中的作用

在触控交互中,缺少触觉反馈会造成用户操作水平的降低和用户体验的下降.前人研究对在触控交互中增加触觉反馈这一方法进行了探索.然而,由于现有触摸屏技术仅能在用户点击屏幕后检测用户手指的位置,触觉反馈也只能在用户点击屏幕之后发挥作用.新的传感技术可以在触摸屏上方的悬浮空间(hover space)内提前检测到手指的位置.利用多对象选择任务(multi-target pointing task)比较了在悬浮空间中增加4种反馈方式对用户操作水平和用户体验的影响.实验结果显示,增加的点击振动反馈受到了用户的普遍青睐.然而,增加的触觉反馈对于用户的操作效率和正确率却没有影响.根据这些结果和前人的研究,提出了在悬浮空间中增加触觉反馈的设计建议.     

How should Fitts' Law be applied to human-computer interaction?

The paper challenges the notion that any Fitts' Law model can be applied generally to human-computer interaction, and proposes instead that applying Fitts' Law requires knowledge of the users' sequence of movements, direction of movement, and typical movement amplitudes as well as target sizes. Two experiments examined a text selection task with sequences of controlled movements (point-click and point-drag). For the point-click sequence, a Fitt's Law model that used the diagonal across the text object in the direction of pointing (rather than the horizontal extent of the text object) as the target size provided the best fit for the pointing time data, whereas for the point-drag sequence, a Fitts' Law model that used the vertical size of the text object as the target size gave the best fit. Dragging times were fitted well by Fitts' Law models that used either the vertical or horizontal size of the terminal character in the text object. Additional results of note were that pointing in the point-click sequence was consistently faster than in the point-drag sequence, and that pointing in either sequence was consistently faster than dragging. The discussion centres around the need to define task characteristics before applying Fitts' Law to an interface design or analysis, analyses of pointing and of dragging, and implications for interface design.     

基于菲茨定律的虚拟现实任意形状选择模型

为了评估虚拟现实（VR）交互界面不同图形设计的点击效率，基于概率菲茨定律提出一种针对虚拟现实情境下指向性任务完成时间的预测方法，并构建了VR任意形状选择模型。首先，根据VR界面设计的实际需求，加入形状对指向性任务完成时间的影响，构建命中概率与任务难度指数的关系函数，将目标质心设为待积分函数的中心点，完成虚拟情境下概率菲茨模型定义。然后，设计实验一以获取改进概率菲茨模型中概率函数的常数项值；在此基础上设计实验二计算改进概率菲茨模型中预测函数的常数项，完成改进概率菲茨模型的构建。最后，以某VR烟草分拣系统实际点击任务对模型进行验证与评估，实验结果表明该模型能够在虚拟情境下对任务完成时间进行良好预测。     

基于菲茨定律的虚拟现实任意形状选择模型

为了评估虚拟现实（VR）交互界面不同图形设计的点击效率,基于概率菲茨定律提出一种针对虚拟现实情境下指向性任务完成时间的预测方法,并构建了VR任意形状选择模型。首先,根据VR界面设计的实际需求,加入形状对指向性任务完成时间的影响,构建命中概率与任务难度指数的关系函数,将目标质心设为待积分函数的中心点,完成虚拟情境下概率菲茨模型定义。然后,设计实验一以获取改进概率菲茨模型中概率函数的常数项值;在此基础上设计实验二计算改进概率菲茨模型中预测函数的常数项,完成改进概率菲茨模型的构建。最后,以某VR烟草分拣系统实际点击任务对模型进行验证与评估,实验结果表明该模型能够在虚拟情境下对任务完成时间进行良好预测。     

Agent任务可视编程和单元组合重构

文中将机器人装配单元的各类设备定义为独立的Ａｇｅｎｔ,采用Ｐｅｔｒｉ Ｎｅｔ模型,为各Ａｇｅｎｔ的作业定义了有关操作的基本模型结构,作为基于多Ａｇｅｎｔ的模型库。通过对Ａｇｅｎｔ模型库元素的可视化组合重构,不仅可以实现机器人作业单元几何元素的重组,而且可以方便地实现作业任务的重组。     

Assisting Visually Impaired People to Acquire Targets on a Large Wall-Mounted Display

Large displays have become ubiquitous in our everyday lives, but these displays are designed for sighted people.This paper addresses the need for visually impaired people to access targets on large wall-mounted displays. We developed an assistive interface which exploits mid-air gesture input and haptic feedback, and examined its potential for pointing and steering tasks in human computer interaction（HCI）. In two experiments, blind and blindfolded users performed target acquisition tasks using mid-air gestures and two different kinds of feedback（i.e., haptic feedback and audio feedback）. Our results show that participants perform faster in Fitts＇ law pointing tasks using the haptic feedback interface rather than the audio feedback interface. Furthermore, a regression analysis between movement time（MT） and the index of difficulty（ID）demonstrates that the Fitts＇ law model and the steering law model are both effective for the evaluation of assistive interfaces for the blind. Our work and findings will serve as an initial step to assist visually impaired people to easily access required information on large public displays using haptic interfaces.     

An Empirical Study on the Interaction Capability of Arm Stretching

Body-based motion gestures have been gaining popularity in designing interactive systems. However, theories and design guidelines on the use of body movement in design have not been fully evaluated. This article investigates human ability to perform discrete target selection tasks using stretching action through two controlled experiments. The experimental results indicate that: (1) the range of the discrete levels of depth that users can easily discriminate with arm stretching is up to 16 with full visual feedback, but is down to 4 without the feedback; (2) dwelling, a gesture with keeping a hand motionless and the cursor within a target area for a certain amount of time, may be the best gesture for confirmation command; (3) full visual feedback can improve the user performance; and (4) arm stretching action can be modeled using Fitts’ law. We also discuss the design potentials for Stretch Widgets based on these results.     

Performance in one-, two- and three-dimensional terminal aiming tasks

Arm movement times were measured to targets with independent constraints (target sizes) in one, two or three directions (width, height and depth). In each case, modified forms of Fitts' law give a good fit to the data, with the best form being dependent on all constraints in the 'Weighted Euclidean' model of Accot, J. and Zhai, S., 2003. (Refining Fitts' law models for bivariate pointing. Proceedings of the SIGCHI conference on Human factors in computing systems CHI '03, 5-10 April 2003, Ft. Lauderdale, FL. New York: ACM Press, 193-200). The best predictor includes all the individual ratios of amplitude of movement to target dimension related to the various constraints, with the maximum portion of variance accounted for by the index of difficulty (ID) in the direction of motion. The suggestion by various authors that the maximum of the ID associated with the different constraints will determine the movement times is only partially successful. An explanation for the results is given in terms of control strategy and the form of target. STATEMENT OF RELEVANCE: In many tasks, workers move objects into limited spaces that allow only a single entry area. Termination of the movement may have constraints in one, two or three dimensions. Movement times for such tasks are important to predict industrial performance, and guide task designers in reducing physical constraints on performance.     

Multimodal feedback: an assessment of performance and mental workload

Multimodal interfaces offer great potential to humanize interactions with computers by employing a multitude of perceptual channels. This paper reports on a novel multimodal interface using auditory, haptic and visual feedback in a direct manipulation task to establish new recommendations for multimodal feedback, in particular uni-, bi- and trimodal feedback. A close examination of combinations of uni-, bi- and trimodal feedback is necessary to determine which enhances performance without increasing workload. Thirty-two participants were asked to complete a task consisting of a series of 'drag-and-drops' while the type of feedback was manipulated. Each participant was exposed to three unimodal feedback conditions, three bimodal feedback conditions and one trimodal feedback condition that used auditory, visual and haptic feedback alone, and in combination. Performance under the different conditions was assessed with measures of trial completion time, target highlight time and a self-reported workload assessment captured by the NASA Task Load Index (NASA-TLX). The findings suggest that certain types of bimodal feedback can enhance performance while lowering self-perceived mental demand.     

一种基于深度学习的表情识别方法

针对人脸表情识别鲁棒性差,容易受身份信息干扰的问题,提出一种具有局部并行结构的深度神经网络识别算法。首先使用稀疏自编码算法训练得到不同尺度的卷积核,然后提取卷积核特征并作池化处理,使特征具有一定的平移不变性,最后采用与表情相关的7个并行的4层网络得到最终的分类结果。实验结果表明,在标准的人脸表情识别库上进行独立测试时,本文提出的局部并行深度神经网络的表情识别方法对测试集的人不出现在训练集中的情况有较好表现,相比其他算法更具有实用性。     

Multimodal feedback: an assessment of performance and mental workload

Multimodal interfaces offer great potential to humanize interactions with computers by employing a multitude of perceptual channels. This paper reports on a novel multimodal interface using auditory, haptic and visual feedback in a direct manipulation task to establish new recommendations for multimodal feedback, in particular uni-, bi- and trimodal feedback. A close examination of combinations of uni-, bi- and trimodal feedback is necessary to determine which enhances performance without increasing workload. Thirty-two participants were asked to complete a task consisting of a series of ‘drag-and-drops’ while the type of feedback was manipulated. Each participant was exposed to three unimodal feedback conditions, three bimodal feedback conditions and one trimodal feedback condition that used auditory, visual and haptic feedback alone, and in combination. Performance under the different conditions was assessed with measures of trial completion time, target highlight time and a self-reported workload assessment captured by the NASA Task Load Index (NASA-TLX). The findings suggest that certain types of bimodal feedback can enhance performance while lowering self-perceived mental demand.