IMM-PF visual tracking based on multi-feature fusion

被引：0

作者：

Dhassi, Younes ^{[1
]}

Aarab, Abdellah ^{[1
]}

Alfidi, Mohammed ^{[2
]}

机构：

[1] Sidi Mohamed Ben Abdellah Univ, Fac Sci Dhar Mahraz, Dept Phys, Lab Elect Signals Syst & Comp, Fes, Morocco

[2] Sidi Mohamed Ben Abdellah Univ, Natl Sch Appl Sci, Engn Lab Syst & Applicat, Fes, Morocco

来源：

2016 11TH INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEMS: THEORIES AND APPLICATIONS (SITA) | 2016年

关键词：

Visual tracking; Multi-feature fusion; Particle filter; IMM; PARTICLE FILTER; MODEL;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

To overcome the tracking problems caused on the one hand by the complex environment and target's appearance changes and on the other hand by maneuvering motion, tracking algorithm was proposed based on multi-feature fusion for particle filter to construct a robust appearance model, and a multi dynamic model under the interactive multiple models (IMM) to describe the target's motion. The proposed method is tested on a variety of videos that present different conditions. Experiences and comparisons conducted show the robustness of our methods in different tracking conditions.

引用

页数：6

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