JournalSignal Processing: Image Communication
DateNovember 2013
Author(s)Marina Georgia Arvanitidou, Michael Tok, Alexander Glantz, Andreas Krutz and Thomas Sikora
TitleMotion-based object segmentation using hysteresis and bidirectional inter-frame change detection in sequences with moving camera
AbstractWe present an unsupervised motion-based object segmentation algorithm for video sequences with moving camera, employing bidirectional inter-frame change detection. For every frame, two error frames are generated using mo- tion compensation. They are combined and a segmentation algorithm based on thresholding is applied. We employ a simple and effective error fusion scheme and consider spatial error localization in the thresholding step. We find the optimal weights for the weighted mean thresholding algorithm that enables unsupervised robust moving object segmentation. Further, a post processing step for improving the temporal consistency of the segmentation masks is incorporated and thus we achieve improved performance compared to previously proposed methods. The experimental evaluation and compari- son with other methods demonstrates the validity of the proposed method.
Key wordsmultimedia analysis, inter-frame change detection, object segmentation, hysteresis, global motion estimation