Realization of extreme high presence relay based on intellectual photography

在这项研究中，我们提出了利用Kinect捕捉颜色和深度信息，以视频率自动检测和跟踪注意力玩家(头发、人脸和头部)的系统。我们的系统同时具有以下三个思想：1)使用一个6D特征向量来统一描述每个像素的3D颜色特征和3D几何特征。2)利用K-均值聚类算法将图像中的像素分为前景(如头发、脸部或头部)和背景。3)毛发跟踪前后前景和背景聚类中心的自动学习和更新。这种能力使得我们的系统可以稳健地跟踪头发，而不依赖于头发的颜色和样式，即使在光照变化的情况下，甚至在头发颜色相似的背景之前也是如此。如果脸部(脸部和头发)被设置为前景，我们的系统就成为脸部(或头部)跟踪系统。

In this research, we propose automatic attention player(hair, face and head) detection and tracking system at video-rate by using Kinect to capture color and depth information. Our system has the following three ideas simultaneously : 1) Using a 6D feature vector to describe both the 3D color feature and 3D geometric feature of each pixel uniformly. 2) Classifying pixels in images into foreground(e. g. hair, face or head) and background with K-means clustering algorithm. 3) Automatic learning and updating the cluster centers of foreground and background before and during hair tracking. This ability makes our system can track hairs robustly, which does not depend on its hair color and style, even under lighting change, and even before a background with similar color of hair. Our system becomes a face(or head) tracking system if the face(face and hair) is set as foreground.