Object Tracking Using Local Multiple Features and a Posterior Probability Measure

Object Tracking Using Local Multiple Features and a Posterior Probability Measure

Object tracking has remained a challenging problem in recent years. Most of the trackers can not work well, especially when dealing with problems such as similarly colored backgrounds, object occlusions, low illumination, or sudden illumination changes in real scenes. A centroid iteration algorithm...

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Bibliographic Details
Main Authors: Wenhua Guo, Zuren Feng, Xiaodong Ren
Format: Article
Language:English
Published: MDPI AG 2017-03-01
Series:Sensors
Subjects:
object tracking
multiple features
posterior probability measure
centroid iteration
Online Access:http://www.mdpi.com/1424-8220/17/4/739

Internet

http://www.mdpi.com/1424-8220/17/4/739

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