Paper Info
Title
Towards human motion capture from a camera mounted on a mobile robot
Abstract
This article describes a multiple feature data fusion applied to a particle filter for marker-less human motion capture (HMC) by using a single camera devoted to an assistant mobile robot. Particle filters have proved to be well suited to this robotic context. Like numerous approaches, the principle relies on the projection of the model's silhouette of the tracked human limbs and appearance features located on the model surface, to validate the particles (associated configurations) which correspond to the best model-to-image fits. Our particle filter based HMC system is improved and extended in two ways. First, our estimation process is based on the so-called AUXILIARY scheme which has been surprisingly seldom exploited for tracking purpose. This scheme is shown to outperform conventional particle filters as it limits drastically the well-known burst in term of particles when considering high dimensional state-space. The second line of investigation concerns data fusion. Data fusion is considered both in the importance and measurement functions with some degree of adaptability depending on the current human posture and the environmental context encountered by the robot. Implementation and experiments on indoor sequences acquired by an assistant mobile robot highlight the relevance and versatility of our HMC system. Extensions are finally discussed.
Year
DOI
Venue
2011
10.1016/j.imavis.2011.01.003
Image Vision Comput.
Keywords
Field
DocType
data fusion,towards human motion capture,investigation concerns data fusion,conventional particle filter,hmc system,particle filter,assistant mobile robot,multiple feature data fusion,marker-less human motion,tracked human limb,current human posture,computer vision,state space,mobile robot,particle filtering
Adaptability,Computer vision,Pattern recognition,Silhouette,Particle filter,Sensor fusion,Artificial intelligence,Robot,Monte Carlo localization,Mobile robot,Mathematics,Feature data
Journal
Volume
Issue
ISSN
29
6
Image and Vision Computing
Citations 
PageRank 
References 
5
0.52
31
Authors
3
Name
Order
Citations
PageRank
Paulo Menezes1667.68
Fr&#233/d&#233/ric Lerasle250.86
Jorge Dias355651.00