A Surface-Growing Approach to Multi-View Stereo Reconstruction

By Martin Habbecke, Leif Kobbelt. 2007

161 citations recorded by the source corpus.

Subfields: Aerospace Engineering, Computer Vision and Pattern Recognition

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In Computer Vision and Pattern Recognition

Citations in the corpus

SurfaceNet: An End-to-End 3D Neural Network for Multiview Stereopsis (2017, methodology): “In available multiview stereo pipelines, sparse features are first detected and then propagated to a dense point cloud for covering the whole surface [8, 11], or multiview depth maps are first computed followed with a depth map fusion step to obtain the 3D reconstruction of the object [15, 17].”
Multi-View Stereo for Community Photo Collections (2007, background): “Hornung and Kobbelt [10] propose a sample-and-fit approach to estimate planes and higher-order surfaces for photo-consistency computations.”
Using Multiple Hypotheses to Improve Depth-Maps for Multi-View Stereo (2008, background): “region growing and filtering to build up a final dense surface [13, 15, 16].”
Continuous depth estimation for multi-view stereo (2009, methodology): “Scaled window matching technique proposed by Bradley [5], and plane fitting optimization suggested by Habbecke [11] are also schemes that can rectify matching window or distorted color consistency matching in acceptable time.”
OctoMap: an efficient probabilistic 3D mapping framework based on octrees (2013, methodology): “, 2007) or Surfels (Habbecke and Kobbelt, 2007) were recently used for 3D path planning (Stoyanov et al.”
Manipulator and object tracking for in-hand 3D object modeling (2011, methodology): “They have been used with much success in reconstruction (e.g. Habbecke and Kobbelt, 2007; Weise et al., 2009) largely due to their conceptual simplicity and ease of implementation.”
Multi-View Stereo: A Tutorial (2015, background): “MVS algorithms went through two major developments that took them to their current state: They left the laboratory setting to a small-scale outdoor scenes [174, 102, 85, 169, 190], e.”