Extended Patch Prioritization for Depth Filling Within Constrained Exemplar-Based RGB-D Image Completion

Atapour-Abarghouei, A; Breckon, TP

doi:10.1007/978-3-319-93000-8_35

Extended Patch Prioritization for Depth Filling Within Constrained Exemplar-Based RGB-D Image Completion

Lookup NU author(s): Dr Amir Atapour Abarghouei ORCiD

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This is the authors' accepted manuscript of a conference proceedings (inc. abstract) that has been published in its final definitive form by Springer, Cham, 2018.

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Abstract

We address the problem of hole filling in depth images, obtained from either active or stereo sensing, for the purposes of depth image completion in an exemplar-based framework. Most existing exemplar-based inpainting techniques, designed for color image completion, do not perform well on depth information with object boundaries obstructed or surrounded by missing regions. In the proposed method, using both color (RGB) and depth (D) information available from a common-place RGB-D image, we explicitly modify the patch prioritization term utilized for target patch ordering to facilitate improved propagation of complex texture and linear structures within depth completion. Furthermore, the query space in the source region is constrained to increase the efficiency of the approach compared to other exemplar-driven methods. Evaluations demonstrate the efficacy of the proposed method compared to other contemporary completion techniques.