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Head Gesture Recognition System Using Adaboost Algorithm with Obstacle Detection

机译:带有障碍物检测的Adaboost算法的头部手势识别系统

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摘要

Head gesture recognition is the challenging task of research in the computer vision, mainly for the purpose of head gesture recognition of handicapped peoples using intelligent wheelchair or for the security purpose and human computer interaction. In this paper, an attempt is made to propose a system to recognize head gesture in real time from the video sequences using adaboost algorithm. The proposed system is based on a sequence of four main stages: data acquisition that is image capturing, pre processing means filtering, feature extraction that is rectangular features and a parallel stage with a cascade of classifiers design and classification. Various experiments were performed and the results demonstrate that, the system can successfully recognize head gestures using adaboost algorithm. The gesture recognition from the video sequences is one of the most important challenges in the computer vision. It offers to the system, the ability to identify, recognize and interpret the human head gestures in order to control some devices.
机译:手势识别是计算机视觉研究中的一项具有挑战性的任务,主要用于使用智能轮椅的残疾人的手势识别或出于安全目的和人机交互。在本文中,尝试提出一种使用adaboost算法从视频序列实时识别头部手势的系统。所提出的系统基于四个主要阶段的序列:数据采集即图像捕获,预处理意味着滤波,特征提取即矩形特征以及具有级联分类器设计和分类的并行阶段。进行了各种实验,结果表明,该系统可以使用adaboost算法成功识别头部手势。视频序列中的手势识别是计算机视觉中最重要的挑战之一。它为系统提供了识别,识别和解释人头手势的能力,以便控制某些设备。

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