使用Kinect识别希腊手语词汇

Nikolaos Gkigkelos, C. Goumopoulos
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引用次数: 6

摘要

无论是跟踪连续的手势(交流模式)还是单个单词(翻译模式),手语识别都是一个具有挑战性的问题。我们开发了一个系统,可以使用Kinect技术在翻译模式下识别希腊手语词汇。传感器捕获三维手部运动轨迹,然后将身体关节形式的一组特征馈送到分类器以识别输入符号。在使用最近邻方法进行匹配之前,标准化用于使用动态时间翘曲算法对齐测试和存储轨迹。所涉及的算法的低计算复杂度允许构建具有实时响应时间的系统。该系统以5个人为样本进行了评估,能够识别希腊手语的15个标志。对不同配置进行了测试,准确度达到99.33%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Greek sign language vocabulary recognition using Kinect
Sign language recognition is a challenging problem both when tracking continuous signs (communication mode) or single words (translation mode)1. We have developed a system that can recognize Greek sign language vocabulary in translation mode using Kinect technology. The sensor captures 3D hands movement trajectory and then a set of features in the form of body joints are fed to a classifier to recognize the input sign. Normalization is used to align test and stored trajectories using the dynamic time warping algorithm before matching is done using the Nearest-Neighbor approach. The low computational complexity of the involved algorithms allows for building a system with real-time response times. The system was evaluated with a sample of 5 individuals and is capable of recognizing 15 signs of the Greek sign language. Different configurations were tested and the best accuracy achieved was 99.33%.
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