基于视觉的手势识别：工业控制应用的理想人机界面

　　基于视觉的手势识别：工业控制应用的理想人机界面

　　嵌入式视觉是基于计算机视觉系统的进化和外推，它处理和解释静态图像和视频图像的意义，有望成为下一个重大的技术成功故事。例如，考虑现在在蜂窝电话、平板电脑、笔记本电脑和专用计算机显示器中常见的图像传感器和处理器。最初用于视频会议和摄影，他们现在被用于其他应用程序，如增强现实。［ 1 ］。

　　同样，考虑新兴流行的消费监控系统，由摄像机和其子系统的持续改进的驱动，以及越来越人性化相关的监控软件和服务。［ 2 ］，谁最近已经知道买汽车，图像传感器在车辆周围许多地方越来越发现，利用泊车辅助、后视安全，即将发生的碰撞预警，车道偏离警告等功能。［ 3 ］

　　同样强大的功能和成本效益的图像传感器，处理器，内存设备，I/O收发器，以及在前面提到的系统中使用的其他集成电路同样适用于视觉包容性工业自动化应用开发人员。基于手势的人机界面在许多方面都是理想的，因此在这种环境中越来越普遍。一方面，他们是直观的；为什么要点击鼠标、按钮，甚至滑动手指在触摸屏上翻页或在菜单页中移动，而不是只在空中扫你的手。

　　A gesture-based UI also dispenses with the environmental restrictions that often hamper a touch-based interface; water and other fluids， non-conductive gloves， dirt and germs， etc. However， a first-generation motion implementation such as that utilized by the Nintendo® Wii™ game console system has limitations of its own. An easy-to-lose， breakable， in-hand controller is required to implement the scheme. Additionally， the interface between the controller and the system， usually implemented via Bluetooth®， ZigBee® or some other RF wireless technology， is （like a touchscreen interface） vulnerable to functional degradation due to environmental EMI.

　　Instead， consider an image sensor-inclusive design. Vision-based gesture interfaces use the human body as the controller versus a dedicated piece of extra hardware， interpreting hand， arm， and other body movements. They are comparatively EMI-immune; all that you need to ensure is sufficient operator-to-equipment distance along with adequate ambient lighting. In addition to gesture-based control， and as with the earlier mentioned computers and cell phones， you can use facial recognition technology to not only “unlock” the system in response to the presence of a valid operator‘s visage but also custom-configure the system on the fly for any particular operator， logging into a specific user account， for example.［4］ They can also offer a more extensive suite of user control options than does a coarser-grained accelerometer- or gyroscope-based motion interface.