Abstract
Inspired by recent successes in parallelized optic flow estimation, we propose a variational method which allows to directly estimate dense depth fields from a single hand-held camera in real-time conditions. In particular we show how the central ingredient of the corresponding optic flow method, namely a thresholding scheme, can be generalized to the problem of geometric reconstruction considered in this paper and how it can be parallelized on recent graphics cards. We compare alternative parallelization strategies and experimentally validate that high-quality depth maps can be computed in a few milliseconds from a hand-held camera.
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Stühmer, J., Gumhold, S., Cremers, D. (2012). Parallel Generalized Thresholding Scheme for Live Dense Geometry from a Handheld Camera. In: Kutulakos, K.N. (eds) Trends and Topics in Computer Vision. ECCV 2010. Lecture Notes in Computer Science, vol 6554. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35740-4_35
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DOI: https://doi.org/10.1007/978-3-642-35740-4_35
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