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Durham University

Computer Science


Publication details for Professor Toby Breckon

Atapour-Abarghouei, A. & Breckon, T.P. (2017), DepthComp: Real-time Depth Image Completion Based on Prior Semantic Scene Segmentation, 28th British Machine Vision Conference (BMVC) 2017. London, British Machine Vision Association (BMVA).

Author(s) from Durham


We address plausible hole filling in depth images in a computationally lightweight
methodology that leverages recent advances in semantic scene segmentation. Firstly, we
perform such segmentation over a co-registered color image, commonly available from
stereo depth sources, and non-parametrically fill missing depth values based on a multipass
basis within each semantically labeled scene object. Within this formulation, we
identify a bounded set of explicit completion cases in a grammar inspired context that
can be performed effectively and efficiently to provide highly plausible localized depth
continuity via a case-specific non-parametric completion approach. Results demonstrate
that this approach has complexity and efficiency comparable to conventional interpolation
techniques but with accuracy analogous to contemporary depth filling approaches.
Furthermore, we show it to be capable of fine depth relief completion beyond that of
both contemporary approaches in the field and computationally comparable interpolation