Transferable belief model for hair mask segmentation

Cedric Rousset (1) , Pierre-Yves Coulon (2) , Michèle Rombaut (2)

1 GIPSA-lab - Grenoble Images Parole Signal Automatique
2 GIPSA-AGPIG - GIPSA - Architecture, Géométrie, Perception, Images, Gestes

In this paper, we present a study of transferable belief model for automatic hair segmentation process. Firstly, we recall the transferable Belief Model. Secondly, we defined for the parameters which characterize hair (Frequency and Color) a Basic Belief assignment which represents the belief that a pixel was or not a hair pixel. Then we introduce a discounting function based on the distance to the face to increase the reliability of our sensors. At the end of this process, we segment the hair with a matting process. We compare the process with the logical fusion. Results are evaluated using semi-manual segmentation references

Mots clés: Hair segmentation; Data Fusion; Transferable Belief Model

Domaines: Traitement du signal et de l'image [eess.SP]; Traitement du signal et de l'image [eess.SP]

Cedric Rousset, Pierre-Yves Coulon, Michèle Rombaut. Transferable belief model for hair mask segmentation. ICIP 2010 - 17th IEEE International Conference on Image Processing, Sep 2010, Hong Kong, Hong Kong SAR China. pp.n.c. ⟨hal-00530156⟩