Global Motion Estimation Using a New Motion Vector Outlier Rejection Algorithm

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.