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Gesture recognition is mainly apprehensive on analyzing the functionality ofhuman wits. The main goal of gesture recognition is to create a system whichcan recognize specific human gestures and use them to convey information or fordevice control. Hand gestures provide a separate complementary modality tospeech for expressing ones ideas. Information associated with hand gestures ina conversation is degree,discourse structure, spatial and temporal structure.The approaches present can be mainly divided into Data-Glove Based and VisionBased approaches. An important face feature point is the nose tip. Since noseis the highest protruding point from the face. Besides that, it is not affectedby facial expressions.Another important function of the nose is that it is ableto indicate the head pose. Knowledge of the nose location will enable us toalign an unknown 3D face with those in a face database. Eye detection isdivided into eye position detection and eye contour detection. Existing worksin eye detection can be classified into two major categories: traditionalimage-based passive approaches and the active IR based approaches. The formeruses intensity and shape of eyes for detection and the latter works on theassumption that eyes have a reflection under near IR illumination and producebright/dark pupil effect. The traditional methods can be broadly classifiedinto three categories: template based methods,appearance based methods andfeature based methods. The purpose of this paper is to compare various humanGesture recognition systems for interfacing machines directly to human witswithout any corporeal media in an ambient environment.

Survey on Various Gesture Recognition Techniques for Interfacing Machines Based on Ambient Intelligence