CAJ | 학술논문

为在虚拟维修训练中实现更加自然高效的人机交互，增强维修训练人员的沉浸感，提出一种基于Kinect深度图像和骨骼数据的手势识别方法。通过对维修样机和维修资源的维修特征进行研究，建立基于维修特征的维修动作集合，定义维修操作的常用手势库；在分析和构建手势识别系统流程的基础上，结合Kinect深度图像和骨骼数据实现手势图像的分割，基于形态学闭运算完成手势分割图的预处理，采用Zernike矩的方法实现对常用手势的识别。将该方法应用于机械设备的虚拟维修训练中，结果验证了该方法的可行性和有效性。
위재허의유수훈련중실현경가자연고효적인궤교호，증강유수훈련인원적침침감，제출일충기우Kinect심도도상화골격수거적수세식별방법。통과대유수양궤화유수자원적유수특정진행연구，건립기우유수특정적유수동작집합，정의유수조작적상용수세고；재분석화구건수세식별계통류정적기출상，결합Kinect심도도상화골격수거실현수세도상적분할，기우형태학폐운산완성수세분할도적예처리，채용Zernike구적방법실현대상용수세적식별。장해방법응용우궤계설비적허의유수훈련중，결과험증료해방법적가행성화유효성。
To reinforce the training personnel’s immersion in the virtual maintenance training ,a method for hand recognition based on the depth image and skeleton data from the Microsoft Kinect was presented to achieve more natural and efficient human‐computer interaction .Four sets of maintenance actions based on maintenance characteristics were established with the researches of maintenance characteristics of prototypes and resources in the virtual maintenance scene and the common gestures in the main‐tenance operation were obtained and defined according to these sets .A method for the hand segmentation combining the depth image with skeleton data was proposed on the basis of analyzing and designing the hand recognition system process .The pre‐pro‐cessing of hand segmentation image was completed using closed operation based on the morphology .The common gestures recog‐nition was realized using Zernike moments .Finally the method was applied to the mechanical equipment’s virtual maintenance training and it is verified to be feasible and effective .