Overcomplete steerable pyramid filters and rotation invariance

By Hayit Greenspan, Serge J. Belongie, Rodney M. Goodman, Pietro Perona, Subrata Rakshit, Charles H. Anderson. 1994

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Citations in the corpus

Invariant Representations without Adversarial Training (2018, neutral): “Early examples include Steerable Filters [8, 11], and later SIFT [16].”
Steerable CNNs (2016, methodology): “Steerable filters were first studied for applications in signal processing and low-level vision (Freeman & Adelson, 1991; Greenspan et al., 1994; Simoncelli & Freeman, 1995).”
Object tracking: A survey (2006, background): “1973] (a 2D histogram which shows the cooccurrences of intensities in a specified direction and distance), Law’s texture measures [Laws 1980] (twenty-five 2D filters generated from five 1D filters corresponding to level, edge, spot, wave, and ripple), wavelets [Mallat 1989] (orthogonal bank of filte”
Evading the Adversary in Invariant Representation (2018, background): “Early examples include Steerable Filters [8, 10], and later SIFT [15].”
A Model of Saliency-Based Visual Attention for Rapid Scene Analysis (1998, methodology): “3): RG(c; s) = j(R(c) G(c)) (G(s) R(s))j (2) BY(c; s) = j(B(c) Y (c)) (Y (s) B(s))j (3) Local orientation information is obtained from I using oriented Gabor pyramids O( ; ), where 2 [0::8] represents the scale and 2 f0 ; 45 ; 90 ; 135 g is the preferred orientation [11].”
Robust Real-Time Face Detection (2001, unknown): “Rectangle features are somewhat primitive when compared with alternatives such as steerable filters (Freeman and Adelson, 1991; Greenspan et al., 1994).”
Object-based visual attention for computer vision (2003, background): “Our work is concerned with the development of efficient mechanisms of visual attention for a machine vision system.”
Dynamic Textures (2003, methodology): “3Most common methods use Gabor filters [18, 5] and steerable filters [14, 36, 15, 35, 17].”