基于二维关节型人体模型和EM算法的人体跟踪(英文)

Human Body Tracking Using EM Based on a 2-D Articulated Body Model

提出一种跟踪单眼图像序列中的行人 ,并恢复其运动参数的新方法 .在跟踪中采用了基于SPM (ScaledPrismatModel)扩展的二维纸板人模型取代三维人体模型 ,以获取更快的计算速度 .作者使用EM算法在概率框架下进行运动估计 ,同时 ,算法也考虑了混合的运动模型和运动约束 ,以减小解的搜索空间 .

Visual tracking of human body movement is a key technology in a number of areas, such as visual surveillance and monitoring. In this paper we present a 2-D model-based method of human body tracking from a monocular video sequence. Morris & Rehg put forward a 2-D scaled prismatic model(SPM) for figure registration which has far fewer singularity problems than 3-D models. Here we extend it in a 2-D cardboard human body model with additional one DOF of width change. Based on this modified 2-D model rather than 3-D model in Bregler & Malik′s work, we also set up a mixture motion model for body movements and then solve motion parameters of the articulated body using EM in a statistical framework, where the model-based kinematic constraints are incorporated in a linear form. Tracking results from real video sequences are encouraging.