Deterministic 3D Human Pose Estimation Using Rigid Structure

  • Jack Valmadre
  • Simon Lucey
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6313)

Abstract

This paper explores a method, first proposed by Wei and Chai [1], for estimating 3D human pose from several frames of uncalibrated 2D point correspondences containing projected body joint locations. In their work Wei and Chai boldly claimed that, through the introduction of rigid constraints to the torso and hip, camera scales, bone lengths and absolute depths could be estimated from a finite number of frames (i.e. ≥ 5). In this paper we show this claim to be false, demonstrating in principle one can never estimate these parameters in a finite number of frames. Further, we demonstrate their approach is only valid for rigid sub-structures of the body (e.g. torso). Based on this analysis we propose a novel approach using deterministic structure from motion based on assumptions of rigidity in the body’s torso. Our approach provides notably more accurate estimates and is substantially faster than Wei and Chai’s approach, and unlike the original, can be solved as a deterministic least-squares problem.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Jack Valmadre
    • 1
  • Simon Lucey
    • 2
  1. 1.University of Queensland, Australia 
  2. 2.Commonwealth Scientific and Industrial Research Organisation (CSIRO)Australia

Personalised recommendations