IEEE Transactions on Pattern Analysis and Machine Intelligence
Nonlinear total variation based noise removal algorithms
Proceedings of the eleventh annual international conference of the Center for Nonlinear Studies on Experimental mathematics : computational issues in nonlinear science: computational issues in nonlinear science
Dense depth recovery from stereo images
ECAI '92 Proceedings of the 10th European conference on Artificial intelligence
The robust estimation of multiple motions: parametric and piecewise-smooth flow fields
Computer Vision and Image Understanding
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume I - Volume I
An Algorithm for Total Variation Minimization and Applications
Journal of Mathematical Imaging and Vision
Structure-Texture Image Decomposition--Modeling, Algorithms, and Parameter Selection
International Journal of Computer Vision
Parallel Tracking and Mapping for Small AR Workspaces
ISMAR '07 Proceedings of the 2007 6th IEEE and ACM International Symposium on Mixed and Augmented Reality
Combined Region and Motion-Based 3D Tracking of Rigid and Articulated Objects
IEEE Transactions on Pattern Analysis and Machine Intelligence
A duality based approach for realtime TV-L1 optical flow
Proceedings of the 29th DAGM conference on Pattern recognition
Real-time dense geometry from a handheld camera
Proceedings of the 32nd DAGM conference on Pattern recognition
International Journal of Computer Vision
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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.