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
Building detection and reconstruction from mid-and high-resolution aerial imagery
Computer Vision and Image Understanding
Photorealistic Scene Reconstruction by Voxel Coloring
International Journal of Computer Vision
A Theory of Shape by Space Carving
International Journal of Computer Vision - Special issue on Genomic Signal Processing
A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms
International Journal of Computer Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Hierarchical Model-Based Motion Estimation
ECCV '92 Proceedings of the Second European Conference on Computer Vision
Multi Viewpoint Stereo from Uncalibrated Video Sequences
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume I - Volume I
Occlusion Detectable Stereo -- Occlusion Patterns in Camera Matrix
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
A Space-Sweep Approach to True Multi-Image Matching
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
Robust Acquisition of 3D Informations from Short Image Sequences
PG '02 Proceedings of the 10th Pacific Conference on Computer Graphics and Applications
Stereo Matching Using Belief Propagation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Efficient graph-based energy minimization methods in computer vision
Efficient graph-based energy minimization methods in computer vision
Global optimization using embedded graphs
Global optimization using embedded graphs
A Maximum-Flow Formulation of the N-Camera Stereo Correspondence Problem
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
A Quasi-Dense Approach to Surface Reconstruction from Uncalibrated Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Geo-Consistency for Wide Multi-Camera Stereo
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Bayesian 3D Modeling from Images Using Multiple Depth Maps
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
A Surface Reconstruction Method Using Global Graph Cut Optimization
International Journal of Computer Vision
A Comparison and Evaluation of Multi-View Stereo Reconstruction Algorithms
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
An Improved Observation Model for Super-Resolution Under Affine Motion
IEEE Transactions on Image Processing
SBA: A software package for generic sparse bundle adjustment
ACM Transactions on Mathematical Software (TOMS)
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We are concerned with dense height map reconstruction from aerial oblique image sequences. This configuration occurs when estimating a DSM (digital surface model) of areas where flying over is not allowed or for updating an on-board DSM, for instance, in trajectory planning with obstacle avoidance. We present a complete process starting from a partially calibrated sequence and leading to an estimated height map. The calibration step consists in refining the extrinsic parameters given by on-board ego-motion sensors (GPS and inertial measurement unit, IMU) by means of interest points tracking and bundle adjustment. We then propose a dense matching process based on the minimization of a multi-view pixelwise similarity criterion combined with a discretized L1-norm or total variation (TV) regularization term. Minimization is conducted thanks to an optimal graph-cut approach. Occlusions are accounted for without additional computational cost by a modification of the similarity criterion based on a dictionary of visibility patterns. Finally, two ways of refinement of the height map are proposed. The first one uses a local similarity minimization followed by non-linear Gaussian smoothing. The second relies on a novel approach to increase the height map resolution which combines multi-view 3-D reconstruction and image super-resolution. This method is validated on various synthetic and real aerial sequences, on either side-looking or forward-looking configurations.