【文件属性】：
文件名称：Tracking Human Position and Lower Body Parts Using Kalman and Particle Filters Constrained by Human Biomechanics
文件大小：1.32MB
文件格式：PDF
更新时间：2013-05-30 07:26:56
Human Position tracking
Abstract—In this paper, a novel framework for visual tracking
of human body parts is introduced. The approach presented
demonstrates the feasibility of recovering human poses with data
from a single uncalibrated camera by using a limb-tracking system
based on a 2-D articulated model and a double-tracking strategy.
Its key contribution is that the 2-D model is only constrained by
biomechanical knowledge about human bipedal motion, instead
of relying on constraints that are linked to a specific activity or
camera view. These characteristics make our approach suitable
for real visual surveillance applications. Experiments on a set of
indoor and outdoor sequences demonstrate the effectiveness of our
method on tracking human lower body parts. Moreover, a detail
comparison with current tracking methods is presented.