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Efficient Intermediate Joint Estimation using the UKF based on the Numerical Inverse Kinematics  

Seo, Yung-Ho (School of Electronics and Computer Engineering, Chonnam National University)
Lee, Jun-Sung (School of Electronics and Computer Engineering, Chonnam National University)
Lee, Chil-Woo (School of Electronics and Computer Engineering, Chonnam National University)
Publication Information
Journal of the Institute of Electronics Engineers of Korea SP / v.47, no.6, 2010 , pp. 39-47 More about this Journal
Abstract
A research of image-based articulated pose estimation has some problems such as detection of human feature, precise pose estimation, and real-time performance. In particular, various methods are currently presented for recovering many joints of human body. We propose the novel numerical inverse kinematics improved with the UKF(unscented Kalman filter) in order to estimate the human pose in real-time. An existing numerical inverse kinematics is required many iterations for solving the optimal estimation and has some problems such as the singularity of jacobian matrix and a local minima. To solve these problems, we combine the UKF as a tool for optimal state estimation with the numerical inverse kinematics. Combining the solution of the numerical inverse kinematics with the sampling based UKF provides the stability and rapid convergence to optimal estimate. In order to estimate the human pose, we extract the interesting human body using both background subtraction and skin color detection algorithm. We localize its 3D position with the camera geometry. Next, through we use the UKF based numerical inverse kinematics, we generate the intermediate joints that are not detect from the images. Proposed method complements the defect of numerical inverse kinematics such as a computational complexity and an accuracy of estimation.
Keywords
Human pose estimation; Inverse kinematics; Unscented Kalman filter; Motion capture;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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