A COLOR FEATURES-BASED METHOD FOR OBJECT TRACKING EMPLOYING A PARTICLE FILTER ALGORITHM

Budi Sugandi, Hyoungseop Kim, Joo Kooi Tan, Seiji Ishikawa, Abdul Halim Hakim, Pandian Vasant, Nader Barsoum
2009 AIP Conference Proceedings  
We proposed a method for object tracking employing a particle filter based on color feature method. A histogram-based framework is used to describe the features. Histograms are useful because they have property that they allow changes in the object appearance while the histograms remain the same. Particle filtering is used because it is very robust for non-linear and non-Gaussian dynamic state estimation problems and performs well when clutter and occlusions are present on the image.
more » ... ya distance is used to weight the samples in the particle filter by comparing each sample's histogram with a specified target model and it makes the measurement matching and sample's weight updating more reasonable. The method is capable to track successfully the moving object in different outdoor environment with and without initial positions information, and also, capable to track the moving object in the presence of occlusion using an appearance condition. In this paper, we propose a color featuresbased method for object tracking based on the particle filters. The experimental results and data show the feasibility and the effectiveness of our method.
doi:10.1063/1.3223931 fatcat:wehs53oavfet5kl46crgh5lusu