Paper Info
Title
Performance evaluation of particle filter based visual tracking.
Abstract
Tracking is a fundamental problem for event recognition. Particle filter (PF) is acknowledged for its efficiency in dealing with multi-modal visual tracking problem of general nonlinear and non-Gaussian system. It therefore emerged as an appealing tool for tracking objects in video sequences. Although many proposals have been put forward to deal with various scenarios and enhance PF convergence properties, it is acknowledged that comprehensive evaluations of the proposals are still lacking. This paper aims to contribute to this ongoing research. Especially, simulated videos were created to analyze the influence of the target appearance according to various noise intensities that entails partial or full occlusion scenarios. In the simulated videos, the experiment provided more accurate conclusions given the range of involved factors, w.r.t target model, similarity measurement, and environmental distraction. To validate the conclusion from the simulated videos, the experiment was also conducted in the benchmark videos.
Year
DOI
Venue
2016
10.3233/JIFS-169087
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
Keywords
Field
DocType
Visual tracking,performance evaluation
Computer vision,Particle filter,Tracking system,Eye tracking,Artificial intelligence,Machine learning,Mathematics
Journal
Volume
Issue
ISSN
31
5
1064-1246
Citations 
PageRank 
References 
1
0.36
16
Authors
2
Name
Order
Citations
PageRank
Jingjing Xiao1444.10
Mourad Oussalah234476.14