流形学习方法及其在头部姿势估计中的应用

流行学习是一种新的数据降维方法,能揭示数据的内在变化规律,其目标是发现嵌入在高维数据空间中的低维流形结构,并给出一个有效的低维表示。目前流形学习以其出色的数据约简与可视化能力得到了越来越多模式识别与机器学习工作者的重视。本文介绍了一些常用的流形学习算法,分析了这些算法的优缺点,并利用流形学习中的局部线性嵌入(LLE)算法于头部姿势估计,取得了较好的识别效果。

Manifold Learning and its Application on Head Pose Estimation

Manifold learning is a new data dimensional reduction method,which can reveal the inherent discipline.Its objective is to discover the low-dimensional manifold structure embedded in high dimensional data space,and give an effective low-dimensional formulating.The current manifold learning method gets more and more attentions in the Pattern Recognition and Machine Learning fields for its outstanding data reduction and visualization capabilities.The basic idea of manifold learning was described and the advantages and disadvantages of these algorithms were analyzed,and the LLE was used to estimate the head pose.A good recognition rate was achieved.