Title: Effective search space reduction for human pose estimation with Viterbi recurrence algorithm

Authors: Guijin Han; Hong Zhu; Jianrong Ge

Addresses: Faculty of Automation and Information Engineering, Xi'an University of Technology, Xi'an, 710048, China; School of Automation, Xi'an University of Posts and Telecommunications, Xi'an, 710121, China ' School of Automation, Xi'an University of Posts and Telecommunications, Xi'an, 710121, China ' Modern Education Technology Centre, Shijiazhuang Vocational Technology Institute, Shijiazhuang, 050000, China

Abstract: In this paper, an efficient algorithm for estimating human pose in static images is presented, which is based on pictorial structure model and Viterbi recurrence algorithm. Our algorithm mainly solves three problems in the process of estimating human pose: 1) for overcoming the influence of illumination change and local deformation, a new part appearance model based on HOG feature and SVM is presented; 2) for reducing search space, a new approach using location prior and matching threshold is presented, which can also achieve increasing the rate of convergence and improving the accuracy of human pose estimation; 3) an inference algorithm using Viterbi recurrence algorithm is designed. Experiments results show this new algorithm is more efficient.

Keywords: human pose estimation; pictorial structure model; Viterbi recurrence algorithm; HOG feature; search space reduction; static images; SVM; support vector machine; illumination changes; local deformation; position; orientation.

DOI: 10.1504/IJMIC.2013.053539

International Journal of Modelling, Identification and Control, 2013 Vol.18 No.4, pp.341 - 348

Published online: 29 Apr 2013 *

Full-text access for editors Access for subscribers Purchase this article Comment on this article