Window-matching techniques with Kalman filtering for an improved object visual tracking

被引：0
|
作者：
Vidal, Flavio B. [1 ]
Casanova Alcalde, Victor H. [1 ]
机构：
[1] Univ Brasilia, Dept Elect Engn, BR-70910900 Brasilia, DF, Brazil
来源：
2007 IEEE INTERNATIONAL CONFERENCE ON AUTOMATION SCIENCE AND ENGINEERING, VOLS 1-3 | 2007年
关键词：
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper describes the development and application of an algorithm for object visual tracking from a sequence of images. The algorithm is based on window-matching techniques using the sum of squared differences (SSD) as a distance-similarity measure, but adding stochastic filtering. The algorithm is then applied for tracking: a vehicle on an urban environment; two people meeting and walking together; a ball on a ping-pong game. It is concluded that incorporating the Kalman filtering greatly improves the tracking performance.
引用
收藏
页码：933 / 938
页数：6
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