JOURNAL ARTICLE

An adaptive mean shift particle filter for moving objects tracking

Xun WangYufei ZhaBI Du-yan

Year: 2007 Journal:   Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE Vol: 6279 Pages: 62794N-62794N   Publisher: SPIE

Abstract

In this paper, we integrate mean shift algorithm into the particle filter as the proposal distribution, and adaptively modify the tracking step according to the process of mean shift algorithm. It can be used through the searching for the most matching region with the feature, such as color, texture, etc, which should first be drawn from the targets. Experiments show that it is an efficient and powerful method for tracking fast moving objects in clutter even with occlusions.

Keywords:
Mean-shift Computer science Clutter Computer vision Particle filter Artificial intelligence Tracking (education) Feature (linguistics) Video tracking Matching (statistics) Filter (signal processing) Pattern recognition (psychology) Object (grammar) Mathematics Radar

Metrics

2
Cited By
0.00
FWCI (Field Weighted Citation Impact)
0
Refs
0.07
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Advanced Measurement and Detection Methods
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Advanced Algorithms and Applications
Physical Sciences →  Engineering →  Control and Systems Engineering
Target Tracking and Data Fusion in Sensor Networks
Physical Sciences →  Computer Science →  Artificial Intelligence

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