Object tracking by applying mean-shift algorithm into particle filtering
2009pp. 550–554
Citations Over Time
Abstract
In the pursuit of robust object tracking, both particle filter and mean-shift algorithm have proven successful approaches. Also both of them have weaknesses. The article presents the integration of mean-shift algorithm with particle filtering during the moving object tracking. In our method mean-shift algorithm is used in the sampling steps of particle filtering, which efficiently reduces the number of sampled particles. That integrates the advantages of mean-shift algorithm and particle filtering. When applied in the moving object tracking, our method proved to be more robust and time saving compared with the conventional particle filtering and mean shift algorithm.
Related Papers
- → Efficient particle filtering for multiple target tracking with application to tracking in structured images(2003)28 cited
- → Object tracking by applying mean-shift algorithm into particle filtering(2009)7 cited
- Improved Resampling Procedure Based on Genetic Algorithm in Particle Filter(2015)
- Particle Filters Based on the Nonlinear Mixed Effect State Space Models(2015)