Minimizing the Reprojection Error in Surface Reconstruction from Images

By Pau Gargallo, Emmanuel Prados, Peter F. Sturm. 2007

110 citations recorded by the source corpus.

Subfields: Computational Mechanics, Computer Graphics and Computer-Aided Design

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In Computational Mechanics

In Computer Graphics and Computer-Aided Design

Citations in the corpus

Learning a Multi-View Stereo Machine (2017, neutral): “In the multi-view setting, early work focused on using silhouette information via visual hulls [32], incorporating photo-consistency to deal with concavities (photo hull) [29], and shape reﬁnement using optimization [55, 50, 7, 15].”
Hierarchical Surface Prediction for 3D Object Reconstruction (2017, methodology): “The common methods can be broadly grouped as implicit volumetric reconstruction [7], [18], [19], [22], [38] or explicit mesh based [9], [12] approaches.”
Minimizing the Multi-view Stereo Reprojection Error for Triangular Surface Meshes (2008, methodology): “Another limitation of the algorithms implemented in [6, 20] is due to the fact that the authors assume that the scene is perfectly Lambertian.”
Photometric Bundle Adjustment for Dense Multi-view 3D Modeling (2014, methodology): “[7, 6] generalized this idea to non-convex surfaces in the framework of Level-Sets.”
Learning a Hierarchical Latent-Variable Model of 3D Shapes (2017, methodology): “With respect to 3D object generation from 2D images, commonly used methods can be roughly grouped into two categories: 3D voxel prediction [45, 44, 13, 32, 5, 16] and mesh-based methods [12, 7].”
Multi-View Stereo: A Tutorial (2015, methodology): “Iterative applications [58, 154, 78, 55] compute the photo-consistency and its gradient on the current geometry.”
An Occupancy-Depth Generative Model of Multi-view Images (2007, background): “Our recent work [12] avoids these problems by explicitly taking into account the visibility changes during the surface evolution.”
Ray Markov Random Fields for image-based 3D modeling: Model and efficient inference (2010, background): “, occlusion) based on initial surface [19] or currently estimated surface [6, 12]; The other approach estimates the visibility based on the probabilistic opacity of the volume (usually for voxel based approach) [4, 15].”