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» Conférences d’après mars 2011 : nouveau site


Séminaire Vision artificielle / Équipe Willow

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Image, Texture, Video & ’Structural’ Completion: from LEGO’s to Combinatorial Optimization
Nikos Paragios (Ecole Centrale, Paris)

30 novembre 2005

Image Completion (often called inpainting) has emerged to be a high level task of low level vision. Such a procedure consists of completing missing content in images. Central idea within such an approach is often the principle of good continuation, which consists of adding content using information from the borders of the area to be inpainted. While such methods can be quite efficient when dealing with smooth content, fail to account for texture while their extension to complete missing content in video as well as 3D is not straightforward. In this talk we propose a novel technique that addresses image renaissance, video inpainting and structure completion through a "multi-level" graph-based matching process. To this end, numerous patches that do present similarities with the local content around the missing part are considered. The selection of these patches is done through a particle filter method to address the task of hypotheses evaluation. These patches are positioned on top of missing segment, ordered depending on their similarity weight, and form in some fashion a multi-layered graph over time. Markov Random Fields are used to formalize inpainting as a labelling estimation problem while a combinatorial approach is used to recover the optimal combination of patches to complete the missing structure. The min-cut max-flow algorithm within the -expansion process is used to determine the optimal cut that, in an implicit fashion, completes the missing image structure. Promising results in image and texture completion demonstrate the potentials of the proposed method.
Joint work with Cedric Allene

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Nikos Paragios Nikos Paragios (Ecole Centrale, Paris)
Laboratoire MAS