Global Motion Estimation Using a New Motion Vector Outlier Rejection Algorithm

被引：0

作者：

Yildirim, Burak ^{[1
]}

Ilgin, Hakki Alparslan ^{[2
]}

机构：

[1] Inönü Bulvari Kirazlidere Mevkii Süleyman Emin, Undersecretariat for Defense Industries, Ankara

[2] Electrical and Electronics Eng. Dept., Ankara University, 06100 Tandoǧan, Ankara

来源：

Advances in Intelligent Systems and Computing | 2013年 / 210卷

关键词：

Dissimilarity Measure; Global Motion Estimation; Motion Vectors; Outlier Rejection;

D O I：

10.1007/978-3-319-00542-3_50

中图分类号：

学科分类号：

摘要：

Global Motion Estimation (GME) is mainly performed in either pixel or compressed domain. Compressed domain approaches usually utilize existing block matching motion data. On the other hand, in compressed domain based GME, there are many unwanted existing outliers because of noise and foreground objects which are obstacle for GME. In this paper, a new motion vector dissimilarity measure is proposed to remove motion vector (MV)-outliers to provide fast and accurate GME. In experimental results, it is shown that proposed method is fairly successive in terms of both accuracy and complexity compared to the state of the art methods. © Springer International Publishing Switzerland 2013.

引用

页码：507 / 515

页数：8

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