Head Pose Estimation Based on Supervised LLE with Image Euclidean Distance
Chen Duan-sheng · Journal of Chinese Computer Systems · 2012
The Locally Linear Embedding(LLE) is a classical manifold learning algorithm.This unsupervised traditional manifold learning algorithm can be introduced to head pose estimation,but there are two disadvantages: neither considering spatial information of image pixels nor using pose information of the face images.Biased manifold embedding is combined with Image Euclidean Distance(IMED) to compute embedding,when the embedded,the poses of test samples are estimated with general regression neural network(GRNN) and multi-variate liner regression.The comparative experiments on FacePix database shows that the proposed method gets better head pose estimation.