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Dynamic Hand Gesture Recognition Based On Randomized Self-Organizing Map Algorithm

机译:基于随机自组织地图算法的动态手势识别

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Gesture recognition is an appealing tool for natural interface with computers especially for physically impaired persons. In this paper, it is proposed to use Self-Organized Map (SOM) to recognize the posture images of hand gestures. Since the competition algorithm of SOM allows alleviating many diaculties associated with gesture recognition. However, it is required to reduce the recognition time of one image in SOM network to the range of normal video camera rates, this permits the network to accept dynamic input images and to perform on-line recognition for hand gestures. To achieve this, the Randomized Self-Organizing Map algorithm (RSOM) is proposed as a new recognition algorithm for SOM. With RSOM algorithm, the recognition time of one image reduced to 12.4 % of the normal SOM competition algorithm with 100 % accuracy and allowed the network to recognize images within the range of normal video rates. The experimental results to recognize six dynamic hand gestures using RSOM algorithm is presented.
机译:手势识别是与特别是对身体障碍者电脑自然的界面吸引人的工具。在本文中,建议采用自组织映射(SOM)来识别手势的姿势图像。由于SOM的竞争算法允许缓和与手势识别相关的许多diaculties。然而,需要一个图像的在SOM网络识别时间减少到正常摄像机率的范围,这允许网络能够接受动态输入图像,并为手势执行在线识别。为了实现这一目标,随机自组织映射算法(RSOM)的建议作为SOM一个新的识别算法。与RSOM算法,一个图像的识别时间减少到100%的准确度的正常SOM竞争算法的12.4%,并允许网络正常视频速率的范围内识别的图像。实验结果认识到使用RSOM算法,六种动态手势。

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