基于环境智能的接口机手势识别技术综述
Survey on Various Gesture Recognition Techniques for Interfacing Machines Based on Ambient Intelligence
摘要：
手势识别主要是对人的智能功能进行分析。手势识别的主要目标是创建一个可以识别特定人类手势的系统，并使用它们来传达信息或用于设备控制。手势提供了一个单独的补充形式，以表达一个人的想法。在会话中与手势相关的信息有程度、语篇结构、时空结构等。目前的方法主要分为基于数据手套的方法和基于视觉的方法。一个重要的面部特征点是鼻尖。因为鼻子是从脸上突出的最高点。除此之外，它不受面部表情的影响。鼻子的另一个重要功能是它能够指示头部姿势。鼻子位置的知识将使我们能够将未知的3D人脸与人脸数据库中的人脸对齐。眼睛检测分为眼睛位置检测和眼睛轮廓检测。现有的人眼检测方法可以分为两大类：传统的基于图像的被动方法和基于红外的主动方法。前者利用眼睛的强度和形状进行检测，后者基于眼睛在近红外照明下具有反射并产生亮/暗瞳孔效应的假设工作。传统的方法大致可以分为三类：基于模板的方法、基于外观的方法和基于特征的方法。本文的目的是比较各种人的手势识别系统接口机器直接到人的智慧，没有任何corpus媒体在周围环境中。
英文摘要：
Gesture recognition is mainly apprehensive on analyzing the functionality of human wits. The main goal of gesture recognition is to create a system which can recognize specific human gestures and use them to convey information or for device control. Hand gestures provide a separate complementary modality to speech for expressing ones ideas. Information associated with hand gestures in a conversation is degree,discourse structure, spatial and temporal structure. The approaches present can be mainly divided into Data-Glove Based and Vision Based approaches. An important face feature point is the nose tip. Since nose is the highest protruding point from the face. Besides that, it is not affected by facial expressions.Another important function of the nose is that it is able to indicate the head pose. Knowledge of the nose location will enable us to align an unknown 3D face with those in a face database. Eye detection is divided into eye position detection and eye contour detection. Existing works in eye detection can be classified into two major categories: traditional image-based passive approaches and the active IR based approaches. The former uses intensity and shape of eyes for detection and the latter works on the assumption that eyes have a reflection under near IR illumination and produce bright/dark pupil effect. The traditional methods can be broadly classified into three categories: template based methods,appearance based methods and feature based methods. The purpose of this paper is to compare various human Gesture recognition systems for interfacing machines directly to human wits without any corporeal media in an ambient environment.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
