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Precise head segmentation on arbitrary backgrounds

: Schneider, D.C.; Prestele, B.; Eisert, P.


Institute of Electrical and Electronics Engineers -IEEE-; IEEE Signal Processing Society:
16th IEEE International Conference on Image Processing, ICIP 2009. Proceedings. Vol.4 : Cairo, Egypt, 7 - 10 November 2009
Piscataway, NJ: IEEE, 2009
ISBN: 978-1-4244-5653-6 (Print)
ISBN: 978-1-4244-5654-3
ISBN: 978-1-4244-5655-0 (USB-Stick)
International Conference on Image Processing (ICIP) <16, 2009, Cairo>
Conference Paper
Fraunhofer HHI ()
image segmentation; iterative methods

We propose a method for segmentation of frontal human portraits from arbitrary unknown backgrounds. Semantic information is used to project the face into a normalized reference frame. A shape model learned from a set of manually segmented faces is used to compute a rough initial segmentation using a fast iterative algorithm. The rough initial cutout is refined with a boundary based algorithm called 'cluster cutting'. Cluster cutting uses a cost function derived from clustering pixels along the normal of the initial segmentation path with a tree-building algorithm. The result can be refined by the user with an interactive variant of the same algorithm.