Marker-Based Human Motion Capture in Multiview Sequences. (22nd November 2010)

• Record Type: Journal Article
• Authors: Canton-Ferrer Canton-Ferrer, Cristian Cristian; Casas Casas, Josep R. Josep R.; Pardàs Pardàs, Montse Montse
• Other Names: Yang Yang Jar Ferr Jar Ferr Academic Editor.
• Is Part Of: EURASIP journal on advances in signal processing. Volume 2010(2010)
• Publication Date: 2010-11-22
• Subjects: Signal processing -- Periodicals; Traitement du signal; Signal processing; Periodicals; 621.3822
• DOI: 10.1155/2010/105476
• Languages: English
• ISSNs: 1687-6172

Abstract

Abstract : This paper presents a low-cost real-time alternative to available commercial human motion capture systems. First, a set of distinguishable markers are placed on several human body landmarks, and the scene is captured by a number of calibrated and synchronized cameras. In order to establish a physical relation among markers, a human body model is defined. Markers are detected on all camera views and delivered as the input of an annealed particle filter scheme where every particle encodes an instance of the pose of the body model to be estimated. Likelihood between particles and input data is performed through the robust generalized symmetric epipolar distance and kinematic constrains are enforced in the propagation step towards avoiding impossible poses. Tests over the HumanEva annotated data set yield quantitative results showing the effectiveness of the proposed algorithm. Results over sequences involving fast and complex motions are also presented.