Object recognition by affine invariant matching
By Y. Lamdan, Jacob T. Schwartz, Haim J. Wolfson. Proceedings CVPR '88: The Computer Society Conference on Computer Vision and Pattern Recognition, 2011
320 citations recorded by the source corpus.
Subfields: Aerospace Engineering, Computer Vision and Pattern Recognition
View Paper: https://www.semanticscholar.org/paper/1f314b8066e4b8248172e0b9c1e73a31588e73f6
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Aerospace Engineering
- Jitendra Malik
- Serge J. Belongie
- Josef Sivic
- Relja Arandjelovi'c
- Ignacio Rocco
- Xiaodan Liang
- D.A. Forsyth
- Liang Lin
In Computer Vision and Pattern Recognition
- Luc Van Gool
- Jitendra Malik
- Xiaogang Wang
- Andrew Zisserman
- Andrea Vedaldi
- Dacheng Tao
- Alan L. Yuille
- Ming-Hsuan Yang
Citations in the corpus
- Finding Pictures of Objects in Large Collections of Images (1996, methodology): “…then be used as an index for a model library (examples of various combinations of geometry, imaging transformations, and indexing strategies include Lamdan et al., 1988; Weiss, 1988; Forsyth et al., 1991; Rothwell et al., 1992; Stein 8c Medioni, 1992; Taubin 8c Cooper, 1992; Liu et al., 1993;…”
- A new point matching algorithm for non-rigid registration (2003, methodology): “, tree searches [2,20], the Hausdorff distance [25], geometric hashing [24,26] and the alignment method [42].”
- Convolutional Neural Network Architecture for Geometric Matching (2017, methodology): “Final geometry estimation is done by RANSAC [18] or Hough voting [32, 34, 38].”
- Delving deeper into the whorl of flower segmentation (2010, unknown): “[15].”
- Toward Characteristic-Preserving Image-based Virtual Try-On Network (2018, methodology): “images form a set of tentative correspondences, (3) these correspondences are used to robustly estimate the parameters of geometric model using RANSAC [7] or Hough voting [16,22].”
- Shape Quantization and Recognition with Randomized Trees (1997, background): “Other successful treatments of invariance include geometric hashing ( Lamdan, Schwartz, & Wolfson, 1988 ) and nearest-neighbor classifiers based on affine invariant metrics (Simard et al., 1994).”