[1]XU Qi,WANG Huabin,ZHOU Jian,et al.Swarm intelligence filtering for robust object tracking[J].CAAI Transactions on Intelligent Systems,2019,14(4):697-707.[doi:10.11992/tis.201805049]
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Swarm intelligence filtering for robust object tracking
CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume:
14
Number of periods:
2019 4
Page number:
697-707
Column:
学术论文—人工智能基础
Public date:
2019-07-02
- Title:
- Swarm intelligence filtering for robust object tracking
- Keywords:
- object tracking; visual tracking; filtering algorithm; Bayesian filter; particle filter; motion model; posterior state; swarm intelligence optimization
- CLC:
- TP391.41
- DOI:
- 10.11992/tis.201805049
- Abstract:
- To estimate the state of target in object tracking, a novel algorithm named swarm intelligence filter (SIF) is proposed in this paper. Based on the Bayesian filter, the algorithm could estimate the posterior state using three movements of swarms. The cohesion movement could add the weight by maintaining the diversity of the sample, and the coordination of separation and permutation movements could more accurately predict the state of the next moment compared with the conventional algorithm. The experimental results show that compared with the conventional particle filter, our algorithm could more accurately predict the posterior state in nonlinear systems and more accurately estimate the state of the object in complex environment.
- References:
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Last Update:
2019-08-25