Survey on Various Gesture Recognition Techniques for Interfacing Machines Based on Ambient Intelligence
Harshith C, Karthik R. Shastry, Manoj Ravindran, M.V.V.N.S. Srikanth,, Naveen Lakshmikhanth

TL;DR
This survey reviews various gesture recognition techniques for machine interfacing in ambient intelligence, comparing data-glove and vision-based approaches, and discussing facial feature detection methods like nose and eye detection.
Contribution
It provides a comprehensive comparison of gesture recognition systems and facial feature detection methods for ambient intelligence interfaces, highlighting their advantages and limitations.
Findings
Data-glove and vision-based approaches are the main categories of gesture recognition.
Facial features like nose tip and eye detection are crucial for face-based gesture analysis.
Traditional eye detection methods include template, appearance, and feature-based techniques.
Abstract
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…
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