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Hybrid gesture recognition system for short-range use

机译:短距离混合手势识别系统

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摘要

In recent years, various gesture recognition systems have been studied for use in television and video games[l]. In such systems, motion areas ranging from 1 to 3 meters deep have been evaluated[2]. However, with the burgeoning popularity of small mobile displays, gesture recognition systems capable of operating at much shorter ranges have become necessary. The problems related to such systems are exacerbated by the fact that the camera's field of view is unknown to the user during operation, which imposes several restrictions on his/her actions. To overcome the restrictions generated from such mobile camera devices, and to create a more flexible gesture recognition interface, we propose a hybrid hand gesture system, in which two types of gesture recognition modules are prepared and with which the most appropriate recognition module is selected by a dedicated switching module. The two recognition modules of this system are shape analysis using a boosting approach (detection-based approach)[3] and motion analysis using image frame differences (motion-based approach)(for example, see[4]). We evaluated this system using sample users and classified the resulting errors into three categories: errors that depend on the recognition module, errors caused by incorrect module identification, and errors resulting from user actions. In this paper, we show the results of our investigations and explain the problems related to short-range gesture recognition systems.
机译:近年来,已经研究了各种手势识别系统以用于电视和视频游戏[1]。在这样的系统中,运动区域的深度范围为1至3米[2]。然而,随着小型移动显示器的迅速普及,能够在更短范围内操作的手势识别系统已经成为必需。在操作过程中用户不知道相机的视场,这加剧了与此类系统有关的问题,这对他/她的动作施加了一些限制。为了克服此类移动摄像头设备产生的限制,并创建更灵活的手势识别界面,我们提出了一种混合手势系统,其中准备了两种类型的手势识别模块,并选择了最合适的识别模块。专用的交换模块。该系统的两个识别模块是使用增强方法的形状分析(基于检测的方法)[3]和使用图像帧差异的运动分析(基于运动的方法)(例如,参见[4])。我们使用样本用户对该系统进行了评估,并将产生的错误分为三类:依赖于识别模块的错误,由于模块标识不正确导致的错误以及由用户操作引起的错误。在本文中,我们显示了调查结果并解释了与短距离手势识别系统有关的问题。

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