You are here

LOW-COST ACCURATE SKELETON TRACKING BASED ON FUSION OF KINECT AND WEARABLE INERTIAL SENSORS

Authors: 

Francois Destelle, Amin Ahmadi, Noel O'Connor, Kieran Moran, Anargyros Chatzitofis, Dimitrios Zarpalas, Petros Daras

Publication Type: 
Refereed Conference Meeting Proceeding
Abstract: 
In this paper, we present a novel multi-sensor fusion method to build a human skeleton. We propose to fuse the joint po- sition information obtained from the popular Kinect sensor with more precise estimation of body segment orientations provided by a small number of wearable inertial sensors. The use of inertial sensors can help to address many of the well known limitations of the Kinect sensor. The precise calcu- lation of joint angles potentially allows the quantification of movement errors in technique training, thus facilitating the use of the low-cost Kinect sensor for accurate biomechani- cal purposes e.g. the improved human skeleton could be used in visual feedback-guided motor learning, for example. We compare our system to the gold standard Vicon optical mo- tion capture system, proving that the fused skeleton achieves a very high level of accuracy.
Conference Name: 
22nd European Signal Processing Conference (EUSIPCO 2014)
Proceedings: 
EUSIPCO 2014
Digital Object Identifer (DOI): 
10.NA
Publication Date: 
01/09/2014
Conference Location: 
Portugal
Research Group: 
Institution: 
Dublin City University (DCU)
Open access repository: 
Yes