Title :
Particle filtering enhanced human tracking on context-aware robotic system
Author :
Kun Wang ; Liu, Xiaoping P.
Author_Institution :
Dept. of Syst. & Comput. Eng., Carleton Univ., Ottawa, ON, Canada
Abstract :
This paper presents the mechanism of visual tracking implemented on a context-aware robotic platform with layered and centralized system architecture. The visual tracking mechanism is developed using Haar-like feature detection algorithm, enhanced by modified Particle Filtering (PF) method, to realize human face tracking and following on a mobile robot platform. Experimental results demonstrate the feasibility and effectiveness of the proposed implementation of visual contexts on the context-aware robotic system.
Keywords :
face recognition; feature extraction; mobile robots; object tracking; particle filtering (numerical methods); robot vision; ubiquitous computing; Haar-like feature detection algorithm; centralized system architecture; context-aware robotic system; human face tracking realization; layered system architecture; mobile robot platform; modified particle filtering method; particle filtering enhanced human tracking; visual tracking mechanism; Context; Filtering; Robot sensing systems; Target tracking; Visualization; context-aware robotics; particle filtering; visual tracking;
Conference_Titel :
Haptic Audio Visual Environments and Games (HAVE), 2013 IEEE International Symposium on
Conference_Location :
Istanbul
Print_ISBN :
978-1-4799-0848-6
DOI :
10.1109/HAVE.2013.6679617
