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Real Time Head Nod and Shake Detection Using HMMs

机译:使用HMM进行实时头点和抖动检测

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摘要

This paper discusses a technique of detecting a head nod and shake. The proposed system is composed of face detection, eye detection and head nod and head shake detection. We use motion segmentation algorithm that makes use of differencing to detect moving people's faces. The novelty of this paper comes from the differencing in real time input images, preprocessing to remove noises (morphological operator and so on), detecting edge lines and restoration, finding the face area and cutting the head candidate. Moreover, we adopt K-means algorithm for finding head. Eye detection extracts the location of eyes from the detected face region. It is performed at the region close to a pair of eyes for real-time eye detecting. Head nod and shake can be detected by HMMs those are adapted by a directional vector. The HMMs vector can also be used to determine neutral as well as head nod and head shake. These techniques are implemented on a lot of images and a notable success is notified.
机译:本文讨论了一种检测头点和抖动的技术。所提出的系统由面部检测,眼睛检测,头部点头和头部抖动检测组成。我们使用运动分割算法,该算法利用差分来检测移动的人脸。本文的新颖之处在于实时输入图像的差异化,预处理以去除噪声(形态算子等),检测边缘线并进行还原,找到面部区域并切割候选头。此外,我们采用K-means算法来查找头部。眼睛检测从检测到的面部区域提取眼睛的位置。在靠近双眼的区域执行以进行实时眼睛检测。 HMM可以检测到头部的点头和晃动,而HMM可以通过方向矢量进行调整。 HMM矢量也可用于确定中性以及头点头和头晃动。这些技术在很多图像上实现,并获得了显着的成功。

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