CAJ | 학술논문

针对复杂环境中的手势识别问题，提出了一种融合深度信息和红外信息的手势识别方法。首先利用Kinect摄像头的深度信息进行动态实时手势分割，然后融合红外图像复原手势区域。解决了实时手势分割和利用手势的空间分布特征进行手势识别时由于分割的手势区域有缺损或有人脸干扰时识别率低的问题。经实验验证，提出的方法不仅不受环境光线的影响，而且可以识别区分度较小的手势，对旋转、缩放、平移的手势识别也具有鲁棒性。对于区分度较大的手势，识别率高达100%。
침대복잡배경중적수세식별문제，제출료일충융합심도신식화홍외신식적수세식별방법。수선이용Kinect섭상두적심도신식진행동태실시수세분할，연후융합홍외도상복원수세구역。해결료실시수세분할화이용수세적공간분포특정진행수세식별시유우분할적수세구역유결손혹유인검간우시식별솔저적문제。경실험험증，제출적방법불부불수배경광선적영향，이차가이식별구분도교소적수세，대선전、축방、평이적수세식별야구유로봉성。대우구분도교대적수세，식별솔고체100%。
Aiming at the problems existed in hand gestures recognition in complex environment, a hand gestures recogni-tion approach fused depth information with infrared information is proposed in this paper. Firstly, depth information captured by Kinect is applied to segment the dynamic hand gesture, then, using infrared image to repair the hand gesture image. It solves the problem of real-time gesture segmentation and low recognition rate of gesture recognition using distribution fea-ture of hand, when there is a defect or face interference in gesture segmentation region. The experimental results show that the proposed method is not sensitive to ambient light, and can identify gestures with small discrimination, and can recognize gesture of rotation, scaling, translation with strong robustness. For those gestures with large discrimination, the recognition rate is up to100%.