2 research outputs found

    User Directed Multi-view-stereo

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    Abstract. Depth reconstruction from video footage and image collec-tions is a fundamental part of many modelling and image-based render-ing applications. However real-world scenes often contain limited texture information, repeated elements and other ambiguities which remain chal-lenging for fully automatic algorithms. This paper presents a technique that combines intuitive user constraints with dense multi-view stereo reconstruction. By providing annotations in the form of simple paint strokes, a user can guide a multi-view stereo algorithm and avoid com-mon failure cases. We show how smoothness, discontinuity and depth ordering constraints can be incorporated directly into a variational opti-mization framework for multi-view stereo. Our method avoids the need for heuristic approaches that edit a depth-map in a sequential process, and avoids requiring the user to accurately segment object boundaries or to directly model geometry. We show how with a small amount of intuitive input, a user may create improved depth maps in challenging cases for multi-view-stereo.

    Color Correction and Depth Based Hierarchical Hole Filling in Free Viewpoint Generation

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