A probabilistic object tracking model based on condensation algorithm

被引：0
|
作者：
Catak, Muammer [1 ]
机构：
[1] Izmir Univ, Dept Elect & Commun Engn, Izmir, Turkey
来源：
SOFT COMPUTING | 2014年 / 18卷 / 12期
关键词：
Condensation algorithm; Variance reduction; Object tracking; Population balances; PARTICLE FILTER;
D O I：
10.1007/s00500-013-1215-3
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Object tracking, which has many application in our daily life, is an important topic in electronics engineering area. It basically deals with estimation and location of an object in given video frames. In this paper, a novel object tracking algorithm based on particle filtering associate with population balances is proposed. The developed algorithm was used to track objects in synthetic frames and natural video frames. According to results, it has high accuracy level for single and multi-object tracking.
引用
收藏
页码：2425 / 2430
页数：6
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