The multiRANSAC algorithm and its application to detect planar homographies

By Marco Zuliani, C. Kenney, Bangalore S. Manjunath. IEEE International Conference on Image Processing 2005, 2005

344 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Environmental Engineering

View Paper: https://www.semanticscholar.org/paper/bef348b975d3f7b7d211d71742d1870edf074597

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Citations in the corpus

MAGSAC++, a Fast, Reliable and Accurate Robust Estimator (2019, background): “de range of vision tasks, e.g., motion segmentation [27], short baseline stereo [27,29], wide baseline matching [19,14,15], detection of geometric primitives [23], image mosaicing [7], and to perform [32] or initialize multi-model ﬁtting [9,18]. In brief, RANSAC repeatedly selects minimal random sub”
Graph-Cut RANSAC (2017, unknown): “to short baseline stereo [27, 29], wide baseline stereo matching [22, 17, 18], motion segmentation [27], image mosaicing [9], detection of geometric primitives [25], multi-model fitting [31], or for initialization of multi-model fitting algorithms [12, 21].”
Energy-Based Geometric Multi-model Fitting (2012, methodology): “In Zuliani et al. (2005) multi- RANSAC required 11604 iterations to fit 4 models to the same data, see Fig.”
Non-iterative approach for fast and accurate vanishing point detection (2009, background): “Since then, most of the works rely on 3D parallelism or orthogonality of dominant structures in the scene to avoid any false detection [2].”
Uncertainty-Driven 6D Pose Estimation of Objects and Scenes from a Single RGB Image (2016, background): “planes) in data with many outliers is an active field of research [34, 9, 18].”
Robust Multiple Structures Estimation with J-Linkage (2008, methodology): “1 Random sampling Minimal sample sets are constructed in a way that neighbouring points are selected with higher probability, as suggested in [9, 2].”
A multi-view probabilistic model for 3D object classes (2009, background): “This can be done by applying an existing feature matching algorithm in all pairs of the viewpoint images [35].”
MAGSAC: Marginalizing Sample Consensus (2018, methodology): “motion segmentation [25], short baseline stereo [25, 27], wide baseline stereo matching [18, 13, 14], detection of geometric primitives [21], image mosaicing [7], and to perform [28] or initialize multi-model fitting [10, 17].”