Robust Rotation and Translation Estimation in Multiview Reconstruction

By Dan Martinec, Tomás Pajdla. 2007 IEEE Conference on Computer Vision and Pattern Recognition, 2007

389 citations recorded by the source corpus.

Subfields: Aerospace Engineering, Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/78b91e035ae601dbd9928c1ecbd8b26c25d52e95

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In Aerospace Engineering

In Computer Vision and Pattern Recognition

Citations in the corpus

Past, Present, and Future of Simultaneous Localization and Mapping: Toward the Robust-Perception Age (2016, neutral): “[245], [254], structure from motion in computer vision [87], [96], [104], [168], and cryo-electron microscopy [224], [225].”
Skeletal graphs for efficient structure from motion (2008, background): “Martinec and Pajdla describe a system for fast, global estimation of camera parameters, but with more controlled data sets than the ones we address here [15].”
Geometry-Aware Learning of Maps for Camera Localization (2017, background): “, bundle adjustment (BA) [22, 23, 39], pose graph optimization (PGO) [8, 17, 37]) in the context of visual SLAM.”
A Survey on Structure from Motion (2017, neutral): “For alternative approaches aiming to resolve the diﬃculties in SfM for symmetric and ambiguous scenes, we refer the reader to other sources, e.g. [14, 66, 60, 45, 55].”
On benchmarking camera calibration and multi-view stereo for high resolution imagery (2008, background): “[8] scored second in the ICCV 2005 challenge “Where am I”.”
CZECH TECHNICAL UNIVERSITY IN PRAGUE (2005, background): “Most of the state of the art techniques for 3D reconstruction from unordered image sets [35, 3, 42, 24] start the computation by performing exhaustive pairwise image matching in order to reveal the structure and connectivity of the data.”
Disambiguating visual relations using loop constraints (2010, methodology): “We utilize a different approach following [9] [16] to obtain globally consistent transformations from relative ones (see Section 5).”
Robust Global Translations with 1DSfM (2014, methodology): “Others use Second Order Cone Programming, based on the l∞ norm [16,17].”
Rotation Averaging (2013, methodology): “The multiple-rotation averaging problem has wide application to the problem of structure-from-motion (SfM), and several papers (Martinec and Pajdla 2007; Sim and Hartley 2006; Hartley and Schaffalitzky 2004; Kahl 2005; Rother and Carlsson 2001; Kaucic et al. 2001; Kahl and Hartley 2008) have…”
SfM with MRFs: Discrete-Continuous Optimization for Large-Scale Structure from Motion (2013, neutral): “These include linear methods for solving for global camera orientations or translations [14], [15], [16] and L 1 methods for solving for camera (and possibly point) positions given known rotations [17], [18].”
SE-Sync: A certifiably correct algorithm for synchronization over the special Euclidean group (2016, methodology): “ntal perceptual problems in robotics; for example, simultaneous localization and mapping (SLAM) [29] and multi-robot localization [3]. Closely-related formulations also arise in structure from motion [24, 31] and camera network calibration [41] (in computer vision), sensor network localization [34],”
Global Motion Estimation from Point Matches (2012, methodology): “Comparison of our spectral method (in red) to [10]’s (blue).”