船舶控制系统中鼠标和触摸屏兼容的接口程序设计

针对高可靠性系统需要同时具备鼠标器和触摸屏输入设备的应用场合,提出了鼠标器和触摸屏兼容的接口程序的设计思想.详细分析了触摸屏接口程序、鼠标驱动程序以及应用接口函数的设计过程,实现了鼠标操作和触摸屏操作的兼容.设计的程序在船舶智能控制系统中获得成功应用,对类似系统输入设备的接口程序设计具有较好的参考意义.     

一种新的鼠标器结构探讨

作为计算机指点式输入设备,目前已有的器械包括：机械式鼠标、光学鼠标、轨迹球、电子笔等。鼠标的应用无疑给人们使用计算机带来了极大便利,但是,由于工作原理的缺陷使得传统鼠标无法应对日益提升的系统应用,比如在三维图形界面下光标定位、控制的实现。本文提出一种新的鼠标器结构,以较小的代价克服了上述传统鼠标器缺点,还实现了三维空间的定位。     

基于单目视觉的虚拟鼠标方法

自然的交互方式有利于提高增强现实系统的真实感和沉浸感,是增强现实技术的重要研究内容。针对这一问题,提出一种基于单目视觉的虚拟鼠标实现方法,只需要使用单个摄像头,即可对裸手手势进行识别进而模拟真实鼠标动作,最后基于该方法开发了基于单目视觉的虚拟鼠标系统。首先,根据色度信息,分割手部肤色区域;然后,基于指尖的形态学特征识别指尖点,并过滤以排除误检点;最后根据指尖点及其坐标控制光标模拟鼠标动作。实验结果表明,该系统设备简单、精度较高,完全可以实现各种鼠标动作的模拟。     

一种新的鼠标器结构探讨

作为计算机指点式输入设备,目前已有的器械包括:机械式鼠标、光学鼠标、轨迹球、电子笔等。鼠标的应用无疑给人们使用计算机带来了极大便利,但是,由于工作原理的缺陷使得传统鼠标无法应对日益提升的系统应用,比如在三维图形界面下光标定位、控制的实现。本文提出一种新的鼠标器结构,以较小的代价克服了上述传统鼠标器缺点,还实现了三维空间的定位。     

基于手势识别算法的鼠标终端

提出了一种基于静态手势与动态手势的识别算法,并结合Windows API的鼠标类函数实现鼠标操作.首先,通过图像处理技术把从摄像头捕捉的原图像转换为可信度较高的二值图像;其次,调用静态手势识别算法识别展开的手指个数,根据手指个数,结合Windows API的鼠标类函数实现鼠标双击及移动功能;最后,当检测到手指个数为5时,调用动态手势识别算法来识别手势的上下左右四个方向,并结合Windows API的鼠标类函数模拟鼠标左右键按下、抬起及滚轮滑动等操作.实验表明,该手势识别算法的识别率达到了94.11%,对于一些开发平台没有鼠标或在使用鼠标不方便的情况下,用手势来替代鼠标输入具有一定的研究价值和意义.     

一种非侵入的GUI自动化测试系统设计

针对嵌入式GUI软件自动化测试,提出一种非侵入的GUI自动化测试系统设计方案,能够使用Python格式的测试脚本灵活描述测试用例的执行步骤,能够自动化执行测试脚本;系统将人机交互步骤转成鼠标键盘模拟设备的控制命令,实现对被测软件鼠标键盘的控制,从而输入需要的人机交互信息,实现测试用例的自动执行;同时以不干扰被测系统为原则,直接采集被测系统输出到显示器中的视频数据,通过对图像数据的处理进行图像对比、图像查找和文字识别,根据测试用例预期输出自动判断用例的执行结果;该测试系统解决了嵌入式软件GUI自动化测试的难题,提高了测试效率。     

多点触控VS鼠标——输入设备你选谁

多点触控以创新的操作方式以及更多的应用功能,在手机上已经得到广泛的应用,其中代表产品就是苹果的iPhone手机,得到了众多粉丝的追捧。随着笔记本触摸板支持多点触摸之后,多点触摸也成为PC上的新输入方式。越来越多的用户习惯甚至是喜欢上多点触控。苹果推出了一款面向台式机用户的触控板产品Magic Track Pad,被众多苹果粉丝追捧不已。最近更是可以破解驱动而应用在PC上,代替鼠标实现输入应用。那么,PC输入多点触控是否能够取代鼠标成为标准的输入设备呢？     

基于MMA7455L加速度鼠标的研究

针对传统鼠标定位必须依靠其所在工作平面的特点,开发出一种利用三向加速度传感器MMA7455L作为移动信号采集的鼠标,使得该鼠标可以脱离平面的束缚正常工作.针对鼠标在PC机屏幕上移动是在平面上的特点,提出了移动补偿算法,可以真正的实现鼠标由平面转向三维空间的自由操作.应用结果表明,该算法与硬件设计能够满足鼠标正常工作的应用要求,并具有性能稳定,成本低廉等优点.     

基于三轴加速计的三维鼠标设计探索

计算机应用领域的扩大,应用需求的种类增多,对计算机的输入也提出了更高的要求。在二维平面运动的传统鼠标已经不能满足更高的人机交互需求,文中基于三轴加速度计ADXL345和Cortex-M0处理器,对三维鼠标的设计进行了探索。通过加速度计ADXL345完成X、Y、Z方向的数据采集,使用I2C将数据传输给Cortex-M0处理器;处理器对数据加工处理后,使用UART将动作的偏移量传输给PC机;根据三维方向的偏移量实现鼠标的三维控制。     

自动配置蓝牙 CSR扩大无线外围设备市场

本报讯记者方华报道11月28日,全球蓝牙连接及无线技术提供商CSR公司宣布推出一种软件解决方案,该方案将加速无线PC外围设备进入大众市场,并与PC捆绑出售。CSR公司的BlueICE(BlueCore Input ConnectionEnhancement,BlueCore增强型输入连接)仅需在蓝牙键盘和鼠标上装上电池,并通过使用其内置BlueCore芯片便可连接主机。在操作系统载入前,BlueICE就可以令键盘和鼠标得以应用,而无需使用有线键盘。据介绍,BlueICE软件主要用于内置BlueCore4-EXT的无线键盘、鼠标和主要界面(内置于PC或连接器内)。PC系统的键盘、鼠标和主要界面采…     

支持多模态交互的桌面增强显示系统

传统的显示设备在受限的物理空间内难以向用户呈现大量画面和复杂内容,而AR头戴式显示设备通过将三维的可视化内容悬浮显示在用户眼前,在不占用额外物理空间的条件下可增强真实世界的画面显示,呈现形式更为丰富的内容。设计AR虚拟空间与真实电脑画面虚实融合的桌面增强显示系统。通过基于二维码识别的空间定位技术将真实电脑画面映射至虚拟空间内,实现交互空间的统一,同时构建窗口布局计算模型使得系统可以根据用户自定义参数自动生成窗口并设置其布局。在此基础上,利用蓝牙通信、网络传输、操作系统底层映射和结合视线检测的语音识别等技术支持手势、键鼠和语音的多模态交互方式,设计鼠标移动策略以扩展鼠标在三维空间下的多种操作模式。实验结果表明,与隔空手势交互、鼠标交互等传统交互方式相比,该系统在处理常见电脑任务时平均耗时节省10%~30%,具有较高的交互效率,且在跨窗口连续移动和瞬间跳转时能够正确显示鼠标位置。     

Head mouse control system for people with disabilities

In this paper, a human–machine interface for disabled people with spinal cord injuries is proposed. The designed human–machine interface is an assistive system that uses head movements and blinking for mouse control. In the proposed system, by moving one's head, the user moves the mouse pointer to the required coordinates and then blinks to send commands. The considered head mouse control is based on image processing including facial recognition, in particular, the recognition of the eyes, mouth, and nose. The proposed recognition system is based on the convolutional neural network, which uses the low-quality images that are captured by a computer's camera. The convolutional neural network (CNN) includes convolutional layers, a pooling layer, and a fully connected network. The CNN transforms the head movements to the actual coordinates of the mouse. The designed system allows people with disabilities to control a mouse pointer with head movements and to control mouse buttons with blinks. The results of the experiments demonstrate that this system is robust and accurate. This invention allows people with disabilities to freely control mouse cursors and mouse buttons without wearing any equipment.     

Local contrast enhancement and adaptive feature extraction for illumination-invariant face recognition

Recognizing human faces in various lighting conditions is quite a difficult problem. The problem becomes more difficult when face images are taken in extremely high dynamic range scenes. Most of the automatic face recognition systems assume that images are taken under well-controlled illumination. The face segmentation as well as recognition becomes much simpler under such a constrained condition. However, illumination control is not feasible when a surveillance system is installed in any location at will. Without compensating for uneven illumination, it is impossible to get a satisfactory recognition rate. In this paper, we propose an integrated system that first compensates uneven illumination through local contrast enhancement. Then the enhanced images are fed into a robust face recognition system which adaptively selects the most important features among all candidate features and performs classification by support vector machines (SVMs). The dimension of feature space as well as the selected types of features is customized for each hyperplane. Three face image databases, namely Yale, Yale Group B, and Extended Yale Group B, are used to evaluate performance. The experimental result shows that the proposed recognition system give superior results compared to recently published literatures.     

Productivity, satisfaction, and interaction strategies of individuals with spinal cord injuries and traditional users interacting with speech recognition software

Speech recognition is an important technology that is becoming increasingly effective for dictation-oriented activities. While recognition accuracy has increased dramatically in recent years, recent studies confirm that traditional computer users are still faster using a keyboard and mouse and spend more time correcting errors than dictating. Further, as these users become more experienced they frequently adopt multimodal strategies that require the keyboard and mouse when correcting errors. While speech recognition can be a convenient alternative for traditional computer users, it can be a powerful tool for individuals with physical disabilities that limit their ability to use a keyboard and mouse. However, research into the performance, satisfaction, and usage patterns of individuals with physical disabilities has not been reported. In this article, we report on a study that provides initial insights into the efficacy of existing speech recognition systems with respect to individuals with physical disabilities. Our results confirm that productivity does not differ between traditional users and those with physical disabilities. In contrast, numerous differences were observed when users rated their satisfaction with the system and when usage patterns were analyzed. Published online: 18 May 2001     

Rule-based cleanup of on-line English ink notes

Recently, many pen-based devices have enabled people to input digital ink naturally. Often, there is smear and correction when writing. This not only makes the document dirty and look unpleasant, but also affects the handwriting recognition when recognition is called for. As the first paper to address the ink cleanup problem, we present our ink cleanup system that removes the smear and correction, so that the document becomes cleaner and more legible and the handwriting recognition rate could also be improved. The algorithms are rule-based and are capable of dealing with the most common cases that may happen during writing, including self-overtracing of a single stroke, inter-overtracing between strokes, correction, touch-up, insertion and wrong writing order. Experimental results show that our system is effective in cleaning the ink note and is promising in increasing the recognition rate as well.     

Multidimensional audio window management

This paper proposes and organization of presentation and control that implements a flexible audio management system we call “audio windows”. The result is a new user interface integrating and enhanced spatial sound presentation system, an audio emphasis system, and a gestural input recognition system. We have implemented these ideas in a modest prototype, also described, designed as an audio server appropriate for a teleconferencing system. Our system combines a gestural front end (currently based on a DataGlove, but whose concepts are appropriate for other devices as well) with an enhanced spatial sound system, a digital signal processing separation of multiple sound sources, augmented with “filtears”, audio feedback cues that convey added information without distraction or loss of intelligibility. Our prototype employs a manual front end (requiring no keyboard or mouse) driving an auditory back end (requiring no CRT or visual display).     

面向大词汇量的实时连续中国手语识别系统

目前手语识别研究的难点之一在于如何实现大词汇量的连续语句识别，针对这个问题，该文提出了几个有效的方法，包括修正转移矩阵，状态结点的捆绑，快速匹配，在搜索路径中加入词跳转的估计参数等。利用上述技术，该文实现了一个基于数据手套和位置跟踪器的大词汇量的连续的中国手语实时识别系统，对中国手语辞典中收录的5100个词以及一批连续语句作实验，实验结果表明，文中所介绍的技术在提高系统识别速度和准确率方面都很有效。     

基于CNN和SVM的人脸识别系统的设计与实现

针对人脸识别在实际应用中存在姿态变化、表情、遮挡等问题,研究了结合支持向量机(SVM)分类的卷积神经网络(CNN)人脸识别算法,设计并实现了人脸识别系统。系统首先使用CNN提取人脸特征向量,再将特征向量通过SVM进行分类。测试结果表明,系统在训练样本充分时面对人脸姿态变化、表情、遮挡等情况下都具有较好的性能,识别率在95%以上,能满足一般的人脸识别需求。     

语音识别技术在电子货架标签系统中的应用

目前卖场中电子货架标签的管理系统主要部署在计算机上,计算机位置相对固定,使用键盘、鼠标交互灵活性不高、操作效率有限,针对以上管理局限,提出了一个基于Android平台和语音识别技术的管理系统设计方案,以提高操作的便携性和工作效率。实验结果表明,该语音管理系统能够以较高的识别性能和操作效率实现对ESL的可移动声控管理,有利于电子货架标签的推广和应用,同时也为基于Android平台的语音识别系统在其他控制领域的应用提供了可供参考的案例和思路。     

Error detection through mouse movement in an online adaptive learning environment

While response time and accuracy indicate overall performance, their value in uncovering cognitive processes, underlying learning, is limited. A promising online measure, designed to track decision-making, is computer mouse tracking, where mouse attraction towards different locations may reflect the consideration of alternative response options. Using a speedy arithmetic multiple-choice game in an online adaptive learning environment, we examined whether mouse movements could reflect arithmetic difficulties when error rates are low. Results showed that mouse movements towards alternative responses in correctly answered questions mapped onto the frequency of errors made in this online learning system. This mapping was stronger for the younger children, as well as for easy arithmetic problems. On an individual level, users showed more mouse movement towards their previously made response errors than towards other alternative options. This opens the possibility of adapting feedback and instruction on an individual basis through mouse tracking.