An improved particle filter based on cuckoo search for visual tracking

Particle filter (PF) has been proven to be a powerful tool to solve visual tracking problem. However, the problem of sample impoverishment is a constraint of PF. To solve this problem, a cuckoo search-based particle filter is proposed. The particles in PF are optimized using cuckoo search. The meani...

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Bibliographic Details
Published in2018 Chinese Control And Decision Conference (CCDC) pp. 3687 - 3691
Main Authors Gui-Xia, Fu, Ming-Liang, Gao, Guo-Feng, Zou, Wen-Can, Liu, Li-Na, Liu
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.06.2018
Subjects
Cuckoo search
Particle degradation
Particle filter
Particle filters
Prediction algorithms
Search problems
Target tracking
Visualization
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Summary:Particle filter (PF) has been proven to be a powerful tool to solve visual tracking problem. However, the problem of sample impoverishment is a constraint of PF. To solve this problem, a cuckoo search-based particle filter is proposed. The particles in PF are optimized using cuckoo search. The meaningful particles are increased and can approximate the true state of the target more accurately. Experiments on visual tracking show that the proposed algorithm outperforms the standard particle filter in solve the visual tracking problems with various challenging conditions.
ISSN:1948-9447
DOI:10.1109/CCDC.2018.8407763