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A Color Features-Based Method for Object Tracking Employing A Particle Filter Algorithm
- Source :
- AIP Conference Proceedings. 1159(1):206-211
- Publication Year :
- 2009
- Publisher :
- AIP Publishing, 2009.
-
Abstract
- 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. Bhattacharyya 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 features‐based method for object tracking based on the particle filters. The experimental results and data show the feasibility and the effectiveness of our method.<br />International Conference on Power Control and Optimization, 1-3, June 2009, Bali, Indonesia
- Subjects :
- particle filter
Computer science
business.industry
color histogram
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
Object (computer science)
Sample (graphics)
Feature (computer vision)
Video tracking
Histogram
Computer Science::Computer Vision and Pattern Recognition
Bhattacharyya distance
Clutter
Computer vision
Artificial intelligence
Particle filter
business
object tracking
Subjects
Details
- Language :
- English
- ISSN :
- 0094243X
- Volume :
- 1159
- Issue :
- 1
- Database :
- OpenAIRE
- Journal :
- AIP Conference Proceedings
- Accession number :
- edsair.doi.dedup.....2b2eb2c4c2cbb33e52d684cc4b95da3a