利用嘴唇轮廓识别面部手势

J. Raheja, Radhey Shyam, Jatin Gupta, Umesh Kumar, P. B. Prasad
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引用次数: 9

摘要

本文描述了一种通过处理包含人脸的图像来确定人类快乐/悲伤/中性面部手势的鲁棒技术。它旨在消除用图像训练计算机的繁琐过程,从而大大减少处理时间。在该技术中,人脸识别是通过在HSV和YCbCr等不同空间上的肤色识别来实现的。利用独特的人脸特征判定方法,确定唇等人脸的分割特征。分析不同人的情绪所形成的嘴唇轮廓,以识别面部手势。唇的边缘检测,然后形态学操作,得到唇的结构。使用独特的直方图算法对嘴唇进行模式分析,然后与不同的面部手势图标进行比较,得出图像中人类的面部手势。在一个巨大的人类图像数据库中,在不同闪电条件下对该技术进行了测试,得出了可接受的准确率,并且发现其速度足够快,可以用于实时视频流
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Facial Gesture Identification Using Lip Contours
This paper describes a robust technique to determine happy/sad/neutral facial gestures of humans by processing an image containing human face. It aims to do away with the cumbersome process of training the computer with images and thereby significantly reducing the processing time. In this technique human face is identified using skin color identification on various spaces like HSV and YCbCr. Segmented features of face like the lips are determined using unique face feature determination. Contour of lips formed for different human moods are analyzed to identify, facial gesture. Edge detection of lips, followed by morphological operation, gives lip structure. Pattern analysis of lips using the unique histogram algorithm and subsequent comparison with different facial gesture icons gives facial gesture of human being in an image. This technique when tested on a huge database of human images under varying lightning conditions gave acceptable accuracy rates and was found fast enough to be used in real time video-stream
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