便捷色彩管理三星CLP-415N

随着办公打印色彩化成为趋势,更多的企业用户纷纷将目光落在彩色激光打印产品身上,考虑着将现有的黑白打印产品升级换代为彩色打印机。2012年,三星数码打印推出11款全新的彩色激光打印产品,多款配置功能不同的新产品适用于不同办公需求的企业用户。而拥有高性价比、高品质输出效果和便捷操作管理的CLP-415N彩色激光打印机将是企业用户的完美选择。     

岳丰08年“华山论剑”之行圆满收尾

日前，YFC-BonEagle岳丰科技出席了08年“华山论剑”的最后一站——南宁站，为岳丰科技在08年圆桌论的画上了圆满的句号。 在论坛上，岳丰中国区销售总部的代表展现了岳丰布线（YFC）全系列代表性产品的展示箱和专利产品——Navilite智能导航配线系统的展示箱，并现场介绍了岳丰的产品系列以及演示了智能导航配线系统的具体使用方法和利用智能导航配线架进行故障诊断的方法，更直观的反映出岳丰智能导航配线系统产品在安装调试和后期维护方面的简单便捷。     

基于双通道表面肌电信号的在线手势识别系统研究

为了获得更加便捷和简单的人机交互方式,采用由Arduino UNO开发板和肌电传感器组成的双通道表面肌电信号采集系统采集手前臂的表面肌电信号,并在上位机中利用MATLAB（R2018b）对采集到的信号进行预处理、活动段检测、特征提取和分类器训练与预测;在识别出手势动作之后,利用GUI界面实时地显示出识别结果。该系统从肌电信号到手势识别、再从手势识别到计算机系统的人机交互方式展现了巨大的潜力和应用空间,尤其是在虚拟现实领域。     

基于视觉的实时手势识别及其在演示控制中的应用

研究基于计算机视觉的实时动态手势识别技术,并利用OpenCV计算机视觉库在VS2010平台上设计一个基于该技术在多媒体教学中PPT演示控制方面的应用。首先,利用背景差分法进行手势检测,在背景更新的基础上,通过背景差分图和颜色直方图的反投影图来检测运动手势区域,可以达到较为满意的实时运动手势检测效果;其次,采用基于颜色直方图的粒子跟踪算法进行手势跟踪,基本能满足跟踪的实时性;最后,在手势识别阶段,采用基于Hu不变矩的轮廓匹配算法,得到较好的手势识别效果;使用六种手势,来实现演示文稿中的控制应用。     

基于手势识别的人机交互发展研究

近年来手势识别技术的快速发展,基于手势识别技术的人机交互应用系统的建立使得人机交互的发展前景广阔.从手形、手势和手形手势的建模出发,介绍了模板匹配、特征提取、神经网络和隐马尔可夫模型4种手势识别的方法,并且综述了基于手势识别技术人机交互的发展,详细介绍了3类人机交互系统：漫游型系统、编辑型系统和操作型系统.     

一种时空多尺度适应的手势识别方法研究

手势交互作为一种自然便捷的交互方式,在智能家居和智能交通等领域具有日益广泛的应用前景。由于手势行为发生的速度、空间约束和用户差异的影响,同一语义手势表现出具有不同时间和空间尺度的多形态特征,这给保障手势识别的准确率带来了挑战。提出了一种基于动态时间规整DTW(Dynamic Time Warping)方法的时空多尺度手势识别方法SDTW(Spatial-Temporal Dynamic Time Warping),该方法通过对空间形态数据进行分箱操作来达到适应一定程度空间尺度变化的能力。因此,SDTW方法不仅具备DTW方法的时间尺度适应性,而且扩展了空间尺度适应性。文中实现了一个基于智能手机加速度传感设备的SDTW手势识别原型系统。实验测试验证了所提方法能够有效提升手势识别的准确率。     

新闻新品

正高性价比惠普打印机为中小企业带来便捷移动打印惠普10月14日宣布推出多款具备移动打印功能的高性价比黑白激光与商用喷墨打印机,帮助中小企业通过移动设备轻松实现移动打印,提升工作效率。此次发布的新品包括HP LaserJet Pro MFP M226系列黑白激光多功能一体机,HP LaserJet Pro M202系列黑白激光打印机以及HP OfficeJet Pro 6230惠商系列彩色办公云打印机。这几款产品全面支持无线直连打印、ePrint及AirPrint,用户不论是在办公室还是在路途中,均可通过智能手机、平板电脑、联网笔记本与电脑等移动终端轻松实现便捷、安全的文印。     

基于WiFi和体感交互的演示系统设计与实现

基于智能手持终端系统内置的三轴陀螺仪捕获手势命令,利用自适应模板匹配方法进行手势识别,在不降低识别率的情况下,提高了识别效率。以WiFi网络作为信息传递载体,将手势命令传输到服务器,以控制演讲时幻灯片的放映。这种基于WiFi和体感交互的演示方式,能克服传统USB激光笔操作方式单一、接收距离有限等问题,提供更好的用户体验。     

提速！佳能引您驶入快车道

佳能新发布的iR1022系列黑白数码复合机产品，正是以适合的价格配合高端产品的品质，为中小型办公环境提供了高性价比的办公产品解决方案。     

基于YOLOv3的手势识别算法

随着手势识别技术和人机交互技术的不断进步,出现了很多人机交互的汽车控制方式。手势交互具有便捷、直观、形象的特点,能够改善传统的方向盘控制模式。基于此,设计基于YOLOv3的手势识别算法。该算法通过优化训练方式调整非极大值抑制（Non-Maximum Suppression,NMS）阈值,进一步提高了手势识别算法的性能。     

基于手势识别的视力检测系统的设计

This design realizes a vision detection system, which can detect human visual acuity through gesture recognition technology. The system includes several modules: acquisition, data storage and conversion, gesture recognition and output control. And the camera, memory, display and speaker are connected externally. The visual icon "E" is displayed on the display screen, and then people use gestures to indicate the direction of "E". After the camera captures the image, the system recognizes and judges the direction of gesture, and then compares the correct direction to detect the visual acuity of people. Because the system eliminates manual detection, it is convenient, accurate and it saves manpower. The system realizes dynamic gesture interaction, being interesting and easy to be popularized.     

基于运动姿态识别的行人惯性导航算法

针对室内定位惯性导航算法存在累积误差的问题,提出了一种基于运动姿态识别的行人惯性导航算法.在捷联惯性导航算法的基础上,引入了行人脚部姿态识别方法,将行人的位移以单步长为单位进行惯性导航解算.使用姿态识别与零速修正相结合确定每一步的静止时刻,改进步数检测结果,并对行人静止时刻的速度和位置信息进行校正,以降低累积误差;统计前期误差较小的行人惯性导航数据,并建立步频—步长模型,根据行人实时的步频和方向变化对当前步长进行校准,在行人以惯常运动姿态或运动姿态变化时分别采取对应的步长估计算法,以保证导航算法的准确性.实验结果表明:与传统捷联惯性导航算法相比,提出的算法提高了长距离导航的精度.     

基于视觉的动态手势识别及其在仿人机器人交互中的应用

手势识别是人和机器人交互中的重要组成部分，本文针对双目视觉系统SFBinoeye实 现了基于光流PCA(主分量分析)和DTW(动态时间规整)的命令手势识别，用以控制仿人机器人 SFHR的手臂运动．利用块相关算法计算光流，并通过主分量分析得到降维的连续投影系数， 与手掌区域的质心位置组合为混合特征向量．针对DTW定义了新的加权距离测度，并用它对 手势进行匹配识别．针对9个手势训练和识别，识别率达到92.4%，并成功地应用于机器人的 手臂控制中．     

Role of laser sensor systems in automation and flexible manufacturing

New industries and production plants require a flexible system, which is capable of picking up objects of various shapes, weights, and colors with arbitrary position and orientation. Such a system also needs recognition and guiding sub-systems. The recognition system includes target function for the recognition sub-system and relation between object characteristics and recognition target. The laser sensor system can be used for such object recognition. Wire-based telemetry and control systems can cause many problems in shop floors and factories, and so there has been a strong growth of interest in wireless guidance like vehicles equipped with laser guiding and navigation systems. For the continuous measurements of parameters such as temperature, etc. optical laser sensor technology seems to become more applicable at this stage. This article describes the operational principles and the use of the most advanced laser sensor systems for quantity measurements, guiding, navigation, pattern recognition, and vision systems for inspection purposes. A variety of laser-based sensors, which can be used as sensing devices in manufacturing, and production technology, are described in this study. Adaptive cruise control systems that can be used in automobile industry to monitor distance and speed are described in this report. As a typical example, the principal operation of a laser guided mobile robot using a laser navigation system is also described.     

Agent system using multimodal interfaces for a smart office environment

This paper presents an experimental study on an agent system with multimodal interfaces for a smart office environment. The agent system is based upon multimodal interfaces such as recognition modules for both speech and pen-mouse gesture, and identification modules for both face and fingerprint. For essential modules, speech recognition and synthesis were basically used for a virtual interaction between user and system. In this study, a real-time speech recognizer based on a Hidden Markov Network (HM-Net) was incorporated into the proposed system. In addition, identification techniques based on both face and fingerprint were adopted to provide a specific user with the service of a user-customized interaction with security in an office environment. In evaluation, results showed that the proposed system was easy to use and would prove useful in a smart office environment, even though the performance of the speech recognizer was not satisfactory mainly due to noisy environments.     

Tracking,recognition, and distance detection of hand gestures for a 3‐D interactive display

Abstract— This study proposes an interactive system for displays, the technologies of which consists of three main parts: hand‐gesture tracking, recognition, and depth measurement. The proposed interactive system can be applied to a general 3‐D display. In this interactive system, for hand‐gesture tracking, Haar‐like features are employed to detect a specific hand gesture to start tracking, while the mean‐shift algorithm and Kalman filter are adopted for fast tracking. First, for recognizing hand gestures, a principal component analysis (PCA) algorithm is used to localize colored areas of skin, and then hand gestures are identified by comparison with a prepared database. Second, a simple optical system is set up with an infrared laser source and a grid mask in order to project a proposed horizontal stripe pattern. Third, the projected patterns are deciphered to extract the depth information using the Hough‐transform algorithm. The system containing hand‐gesture localization, recognition, and associated depth detection (the distance between the display and the hand), was included in a prototype of an interactive display. Demonstration of rotation recognition of a finger‐pointing hand gesture was successful by using the algorithm of radar‐like scanning.     

基于计算机视觉的手势识别康复系统研究与应用

针对目前医学上手部康复治疗的康复器械功能单一,训练过程动作反复且枯燥无趣,恢复过程比较缓慢等问题,提出了一种基于计算机视觉的手势识别康复系统;首先介绍了图像采集、分割、平滑处理、分类、识别等计算机视觉关键技术,其次,重点阐述了手势康复系统的实现细节;通过摄像头采集不同年龄,性别人群手势样本数据,建立康复手势数据库,利用计算机视觉,卷积神经网络,PyQt图形界面等技术来构建康复系统,给出具有趣味性并且高效便利的康复训练方案,治疗方法弥补传统康复治疗的缺陷;实验结果表明,系统运行可靠、准确率高达96％,不但可以提高患者对康复训练的兴趣,积极性,而且价格相对于其他康复器械更加低廉,应用前景更广阔.     

基于Petri网和BPNN的多重触控手势识别

为解决多重触控技术的手势识别问题,提出一个多重触控手势描述与识别框架,给出其描述和识别方法。多重触控手势可分为原子手势和组合手势,在手势描述过程中,利用BP网络对原子手势进行建模,然后在将用户的意图映射为原子手势逻辑、时序和空间关系关联而成的组合手势,并在Petri网引入逻辑、时序和空间关系描述符对组合手势进行描述。在手势识别过程中,根据BP网络分类器检测出原子手势,并触发组合手势Petri网模型的转移,实现组合手势的识别。实验结果表明该方法对不同用户操作习惯有鲁棒性,能有效解决多重触控手势识别问题。     

基于欧氏骨架的手势识别系统

引进最新骨架提取算法,设计并实现了一种以手势的欧氏骨架为基准的手势识别系统,系统由通用视频采集模块和ARM开发板硬件组成.利用动态前景检测算法结合YCbCr肤色识别模型,分割出手势区域;借助欧氏距离变换和Delta—中轴骨架提取算法获得手势区域的欧氏骨架,并提取骨架的关键点和欧氏距离等几何参数,以此建立手势识别的几何模型.实验测试正确识别率高达94%,每帧图片处理时间小于25 ms,表明该系统实时、有效.