一种实时手写数学方程编辑器

该文所述的数学方程编辑器,用户可用笔和书写板输入手写的数学公式,系统通过实时字符、符号识别和图形语法分析软件产生与输入相对应的语法分析树,并由此转换成诸如Latex、数学的或LISP-like符号等输出形式,与基于特殊方程描述语言的编辑系统相比,该手写方程编辑器相对简单且使用方便。     

简谱识别方法研究

简谱是大家非常熟悉和常用的乐谱之一,但是在目前光学乐谱识别领域中对它的研究几乎空白,研究的焦点都集中在五线谱识别上。在深入分析简谱特征的基础上,提出了一整套简谱识别的实现方法。输入的光学简谱经预处理后,首先通过每行的小节线特征提取出简谱部分,然后通过投影法和种子填充算法定位出简谱符号基元的位置,并由此采用不同的识别算法识别出每个简谱符号基元的类型,最后通过组装把各个简谱符号组装成音乐特征符,形成数字化乐谱。实验表明,这套方法对印刷乐谱的识别达到了令人满意的效果,是一项有意义的研究。     

在线双向适应的笔手势界面框架研究

提出一个在线双向适应的笔手势界面框架,该框架针对传统笔手势界面中静态手势识别器不能支持用户的个性化输入以及用户在笔手势界面中面临的手势记忆问题,提出了在线双向适应的策略:一方面系统能够适应用户(系统可以在线支持用户的个性化输入);另一方面用户可以学习系统(用户可以学习系统提供的某些笔手势).该框架包括5个部分:(1)双向适应笔手势输入解释模型;(2)双向适应笔手势输入解释流程;(3)上下文优先级定义;(4)纠错和模糊消解界面;(5)在线笔手势查询帮助系统.在该框架的指导下作者开发了一个原型系统并进行了对比实验评估.结果表明该框架在可用性上具有较大的优势.     

笔式交互和触摸交互的融合策略

针对笔输入能力弱和触摸输入精度低的问题,提出笔式交互与触摸交互的融合策略,并设计了笔+触摸输入技术.首先定性考察笔输入和触摸输入的特性和优劣势,提出2种笔+触摸输入的融合策略;其次基于融合策略设计3种笔+触摸输入技术以及用于参照对比的单笔和单触摸输入技术;再通过3个实验比较这些输入技术的性能.实验结果表明,与单笔或单触摸相比,在颜色改变的直线轨迹任务中,笔+单指触摸、笔+多指触摸和笔+触摸手势的性能分别提升至少90.909%,80.165%和148.209%;在颜色和粗细均改变的圆形轨迹任务中,笔+触摸和笔+手势的任务完成时间比单笔分别减少16.552%和19.705%,而错误率不存在显著差异;在颜色和粗细均改变的绘画任务中,笔+单指触摸、笔+多指触摸和笔+触摸手势的综合指标分别为5.933, 3.333和4.700.最后给出面向笔+触摸输入的交互设计建议、应用场景和改进思路,对笔和触摸的混合输入与界面设计具有指导意义.     

触控、笔和空间手势的混合输入

针对单通道输入条件下输入能力受限的问题,以触控、笔和空间手势为输入通道,提出混合输入技术,允许用户通过双手配合的方式完成操作任务.首先分析了触控、笔和空间手势的性能特点;然后结合不同复杂程度的实际操作环境,提出以笔输入为主的10种双通道和三通道混合输入技术.性能对比的实证研究结果表明,相比于单通道笔式输入,双通道并行输入情况下触控+笔的综合性能最优,双通道二维空间划分下,触控点击+笔的性能最优;包含空间手势的混合输入技术错误率最低,但定性评估结果却最不理想.相关结论对基于触控、笔和空间手势的混合交互和界面设计具有参考意义.     

基于手势识别的文字输入系统

基于视觉的手势识别是实现新一代人机交互的关键技术。通过手势识别向屏幕输入文字以供搜索查找的系统基本没有,在现有的手势识别基础上,利用汉语字母和数字对应的手语作为输入手势,采用微软的kinect获取深度图像,对其进行手势分割。通过Canny算法提取手势的边缘,利用小波矩提取特征,得到手势字母,实现了具有手势识别以及基于文字输入功能的系统。实验表明该系统能够准确有效地实现汉字的输入。     

乐谱识别的预处理和环境参数测定

提出了一种乐谱计算机识别的预处理及环境参数测量的方法。乐谱经归描仪给输入，要作预处理，确定谱表位置、测定谱线宽度、去除噪音、删除谱线等一系列识别前阶段的工作，要为乐谱分割和识别以及自动演奏作好前期准备，计算机系统实验表明，乐谱识别的预处理和环境参数测定是非常有效的。     

基于加速度传感器的大手势集手势识别算法改进研究

搭载着加速度传感器的智能移动终端为手势识别提供广泛的应用平台,在已有的基于单枚加速度传感器的手势识别研究中,识别正确率、速度和手势集合难以达到良好的平衡。本文以一种基于加速度符号序列的识别算法为基础,改进了其特征提取方法,并设计了基于加权树结构模板库的匹配方法,实现了大手势集、高正确率、速度快的手势识别。实验表明,所述系统在21个手势组成的手势集合上,实现了95.2%的用户依赖识别率和94.6%的用户非依赖识别率,识别时间小于10毫秒,对手势识别研究有一定的借鉴价值。     

3D交互输入新技术——手势识别

本文从分析人机交互研究的目的出发 ,介绍了用户产生手势到系统“感知”手势的过程 ,包括手势的建模及识别的原理和方法 .本文在对手结构和手关节运动分析的基础上 ,提出了基于数据手套和基于视觉(摄象机 )的手势输入方式 ,通过手势图象的分析 ,采用模糊神经网络方法对手势图象进行识别 ,取得了较好的效果 ,实现了一种在虚拟环境中具有广阔运用前景的 3D交互输入新技术——手势识别     

Word 2010输入方程式超轻松

如果你想在WORD中输入数学和化学方程式,例如各种数学符号、根号、开方、两次公式等等,最简单的方法是使用方程式编辑器,WORD2010中就内建了方程式编辑器,例如要输入如图1所示公式,在WORD2010中只需以下简单的几步即可搞定!     

3D User Interfaces: New Directions and Perspectives

Three-dimensional user interfaces (3D UIs) let users interact with virtual objects, environments, or information using direct 3D input in the physical and/or virtual space. In this article, the founders and organizers of the IEEE Symposium on 3D User Interfaces reflect on the state of the art in several key aspects of 3D UIs and speculate on future research.     

MAGELLAN: Map Acquisition of GEographic Labels by Legend ANalysis

A system named MAGELLAN (denoting Map Acquisition of GEographic Labels by Legend ANalysis) is described that utilizes the symbolic knowledge found in the legend of the map to drive geographic symbol (or label) recognition. MAGELLAN first scans the geographic symbol layer(s) of the map. The legend of the map is located and segmented. The geographic symbols (i.e., labels) are identified, and their semantic meaning is attached. An initial training set library is constructed based on this information. The training set library is subsequently used to classify geographic symbols in input maps using statistical pattern recognition. User interaction is required at first to assist in constructing the training set library to account for variability in the symbols. The training set library is built dynamically by entering only instances that add information to it. MAGELLAN then proceeds to identify the geographic symbols in the input maps automatically. MAGELLAN can be fine-tuned by the user to suit specific needs. Recognition rates of over 93% were achieved in an experimental study on a large amount of data. Received January 5, 1998 / Revised March 18, 1998     

Recognition of pen-based music notation with finite-state machines

This work presents a statistical model to recognize pen-based music compositions using stroke recognition algorithms and finite-state machines. The series of strokes received as input is mapped onto a stochastic representation, which is combined with a formal language that describes musical symbols in terms of stroke primitives. Then, a Probabilistic Finite-State Automaton is obtained, which defines probabilities over the set of musical sequences. This model is eventually crossed with a semantic language to avoid sequences that does not make musical sense. Finally, a decoding strategy is applied in order to output a hypothesis about the musical sequence actually written. Comprehensive experimentation with several decoding algorithms, stroke similarity measures and probability density estimators are tested and evaluated following different metrics of interest. Results found have shown the goodness of the proposed model, obtaining competitive performances in all metrics and scenarios considered.     

Constructing Chinese characters: keypad design for mobile phones

Increased use of mobile phones and associated services in China highlights the need for effective Chinese input methods for mobile devices. Mapping thousands of characters to a standard telephone keypad is a significant challenge. Structure-based methods provide an appealing known-character/known-code solution, but assigning multiple strokes to each key forces users to learn new, often unfamiliar, mappings. Using an established stroke input method, our study revealed important effects of keypad legend on performance. Novice user performance was evaluated with several alternative keypad designs. The results confirmed that both abstract symbols and concrete examples helped improve the usability of the keypad in Chinese text-entry tasks. Further, combining abstract symbols and concrete examples resulted in performance nearly tripling as compared to the original design. The stroke-to-key mapping accuracy also increased significantly. Handwriting analysis confirmed that the reduced errors are directly associated with the keypad-based text-entry technique.     

国际音标输入软件的设计与实现

文章以蓝蝶国际音标(形类)输入法为对象论述了国际音标输入系统的编码思想、算法设计和字体制作.输入编码的基本原则是字形的分类,合理的分类能产生适合用户的键盘操作习惯;算法设计提出了高频优先的动态连续输入效果;字体制作能及时添加所需字符,并完善字句行距等多文种混排版面质量.     

Constructing Chinese characters: keypad design for mobile phones

Increased use of mobile phones and associated services in China highlights the need for effective Chinese input methods for mobile devices. Mapping thousands of characters to a standard telephone keypad is a significant challenge. Structure-based methods provide an appealing known-character/known-code solution, but assigning multiple strokes to each key forces users to learn new, often unfamiliar, mappings. Using an established stroke input method, our study revealed important effects of keypad legend on performance. Novice user performance was evaluated with several alternative keypad designs. The results confirmed that both abstract symbols and concrete examples helped improve the usability of the keypad in Chinese text-entry tasks. Further, combining abstract symbols and concrete examples resulted in performance nearly tripling as compared to the original design. The stroke-to-key mapping accuracy also increased significantly. Handwriting analysis confirmed that the reduced errors are directly associated with the keypad-based text-entry technique.     

MUSIC,INFORMATION, AND THE GENERAL SYSTEMS PROBLEM SOLVER: A NEW ANALYTIC PERSPECTIVE

Abstract

For nearly four decades, scientists and music theorists have proposed means to express musical style as information. The Shannon entropy has been used for this purpose based upon the following two assertions: (1) musical composition is essentially the selection of musical symbols within sets of constraints, and (2) a compositional process can be characterized mathematically in a general, abstract manner. Such proposals have been widely criticized, principally on the grounds that only limited numbers of parameters are considered in most cases, and then only in terms of how symbols representing pitch, harmony or rhythm are selected independently of the overall relationships which result from such selections. The ways in which pitch, harmony, and rhythm are interrelated is an issue that is virtually ignored. A major premise of the present discussion is that musical style can be expressed as information only in terms of mathematical relations on multiple sets of musical symbols. The General Systems Problem Solver (GSPS), developed by George Klir, may be utilized for this purpose.     

基于嵌入式Linux系统的掌上Emap的设计

本文对基于嵌入式Linux系统下不同的图形用户界面(GUI)进行了综合的介绍和比较,并根据Emap的工作原理,提出了在嵌入式Linux系统下的掌上PDA上运行Emap的一种实现模型,具有较强的实用价值。     

Towards a model-driven approach for multiexperience AI-based user interfaces

Software and Systems Modeling - Software systems start to include other types of interfaces beyond the “traditional” Graphical-User Interfaces (GUIs). In particular, Conversational User...