Title :
An optimal fuzzy system for feature reliability measuring in particle filter-based object tracking
Author :
Komeili, M. ; Valizadeh, M. ; Armanfard, N. ; Kabir, E.
Author_Institution :
Dept. of Electr. Eng., Tarbiat Modarres Univ., Tehran, Iran
Abstract :
In this paper, a fuzzy inference system by which reliability of features can be measured is designed. The reliability determines discriminative power of a feature in separating target from background. We focus our attention on design of membership functions. With a rational explanation on available information over a particle filter-base tracking process, we infer a coarse estimation of membership functions. It follows with a fine-tuning stage by using genetic algorithm. Color, edge, texture and TED are used in current work but the extension to a wider number of features is straightforward.
Keywords :
fuzzy systems; genetic algorithms; inference mechanisms; object detection; particle filtering (numerical methods); tracking; video signal processing; coarse estimation; feature reliability; fuzzy inference system; genetic algorithm; membership function; optimal fuzzy system; particle filter-base tracking process; particle filter-based object tracking; Electric variables measurement; Fuzzy systems; Information filtering; Lighting; Particle filters; Particle measurements; Particle tracking; Power system reliability; Robustness; Target tracking;
Conference_Titel :
Computer Conference, 2009. CSICC 2009. 14th International CSI
Conference_Location :
Tehran
Print_ISBN :
978-1-4244-4261-4
Electronic_ISBN :
978-1-4244-4262-1
DOI :
10.1109/CSICC.2009.5349435