Interactive RGB-D Image Segmentation Using Hierarchical Graph Cut and Geodesic Distance

8 years 10 days ago

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Abstract. In this paper, we propose a novel interactive image segmentation method for RGB-D images using hierarchical Graph Cut. Considering the characteristics of RGB channels and depth channel in RGB-D image, we utilize Euclidean distance on RGB space and geodesic distance on 3D space to measure how likely a pixel belongs to foreground or background in color and depth respectively, and integrate the color cue and depth cue into a uniﬁed Graph Cut framework to obtain the optimal segmentation result. Moreover, to overcome the low eﬃciency problem of Graph Cut in handling high resolution images, we accelerate the proposed method with hierarchical strategy. The experimental results show that our method outperforms the state-of-the-art methods with high eﬃciency.

Ling Ge, Ran Ju, Tongwei Ren, Gangshan Wu

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