Abstract
In this paper, a fast automatic segmentation algorithm based on AdaBoost learning and iterative Graph-Cuts are shown. AdaBoost learning method is introduced for automatically finding the approximate location of certain object. Then an iterative Graph-Cuts method is used to model the segmentation problem. We call our algorithm as AdaBoost Aggregation Iterative Graph-Cuts (AAIGC). Compared to previous methods based on Graph-Cuts, our method is automatic. Once certain object is trained, our algorithm can cut it out from an image containing the certain object. The segmentation process is reliably computed automatically no additional users’ efforts are required. Experiments are given and the outputs are encouraging.
This work has been supported by NSFC Project 60573182, 69883004 and 50338030.
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© 2006 Springer-Verlag Berlin Heidelberg
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Han, D., Li, W., Lu, X., Wang, Y., Zou, X. (2006). Certain Object Segmentation Based on AdaBoost Learning and Nodes Aggregation Iterative Graph-Cuts. In: Perales, F.J., Fisher, R.B. (eds) Articulated Motion and Deformable Objects. AMDO 2006. Lecture Notes in Computer Science, vol 4069. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11789239_20
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DOI: https://doi.org/10.1007/11789239_20
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-36031-5
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