Abstract
In this paper we introduce a novel method for automatic propagation of foreground objects in image sequences. Our method is based on a combination of the mean-shift operator with the well known intelligent scissors technique. It is effective due to the fact that the images are captured with high overlap, resulting in highly redundant scene information. The algorithm requires an initial segmentation of one image of the sequence as an input. In each consecutive image the segmentation of the previous image is taken as an initialization and the propagation procedure proceeds along four major steps. Each step refines the segmentation of the foreground object and the algorithm converges until all images of the sequence are processed. We demonstrate the effectiveness of our approach on several datasets.
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Sormann, M., Zach, C., Bauer, J., Karner, K., Bischof, H. (2005). Automatic Foreground Propagation in Image Sequences for 3D Reconstruction. In: Kropatsch, W.G., Sablatnig, R., Hanbury, A. (eds) Pattern Recognition. DAGM 2005. Lecture Notes in Computer Science, vol 3663. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11550518_12
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DOI: https://doi.org/10.1007/11550518_12
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28703-2
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