Title :
Ubiquitous human motion capture using Wearable micro-sensors
Author_Institution :
Chinese Acad. of Sci., Grad. Univ., Beijing
Abstract :
We have presented our work in progress on human body motion capture using wearable mirco-inertial sensors only. Novel drift model are proposed to deal with inherent bias problem of inertial sensors, and Extended Dynamic Bayesian Network (EDBN) are employed to model the constraints among human body segments. Given the uncertainties of human movements, multiple models are proposed to describe the behaviors of each body segment in the EDBN. The future work will be on consummating our current work. More comprehensive experiments will be further studied to evaluate our proposed method.
Keywords :
image segmentation; image sensors; microsensors; motion estimation; wearable computers; body motion capture; body segments; drift model; extended dynamic Bayesian network; ubiquitous human motion capture; wearable microsensors; wearable mirco-inertial sensors; Bayesian methods; Biological system modeling; Humans; Joints; Magnetic sensors; Motion analysis; Motion estimation; Optical films; Sensor phenomena and characterization; Wearable sensors;
Conference_Titel :
Pervasive Computing and Communications, 2009. PerCom 2009. IEEE International Conference on
Conference_Location :
Galveston, TX
Print_ISBN :
978-1-4244-3304-9
Electronic_ISBN :
978-1-4244-3304-9
DOI :
10.1109/PERCOM.2009.4912807