7.1.8.5 Rotation Invariant Features

Chapter Contents (Back)
Interest Points. Rotation Invariant. Feature Points.

Loy, G., Zelinsky, A.,
Fast radial symmetry for detecting points of interest,
PAMI(25), No. 8, August 2003, pp. 959-973.
IEEE Abstract. 0308
BibRef
Earlier:
A Fast Radial Symmetry Transform for Detecting Points of Interest,
ECCV02(I: 358 ff.).
Springer DOI 0205
BibRef

Liu, W.[Wei], Ribeiro, E.[Eraldo],
Detecting singular patterns in 2D vector fields using weighted Laurent polynomial,
PR(45), No. 11, November 2012, pp. 3912-3925.
Elsevier DOI 1206
Vector fields; Singular-pattern detection; Scale- and rotation-invariance; Complex-valued function; Laurent polynomials BibRef

Xu, X., Tian, L., Feng, J., Zhou, J.,
OSRI: A Rotationally Invariant Binary Descriptor,
IP(23), No. 7, July 2014, pp. 2983-2995.
IEEE DOI 1407
Computer vision BibRef

Zhang, C.H.[Chun-Hui], Liang, J.[Jimin], Zhang, J.[Jun], Zhao, H.[Heng],
A new shape prior model with rotation invariance,
PRL(54), No. 1, 2015, pp. 82-88.
Elsevier DOI 1502
Shape prior model. Keypoints for object detection. BibRef

Anwar, H.[Hafeez], Zambanini, S.[Sebastian], Kampel, M.[Martin],
Efficient Scale- and Rotation-Invariant Encoding of Visual Words for Image Classification,
SPLetters(22), No. 10, October 2015, pp. 1762-1765.
IEEE DOI 1506
BibRef
Earlier:
Encoding Spatial Arrangements of Visual Words for Rotation-Invariant Image Classification,
GCPR14(443-452).
Springer DOI 1411
image classification
See also Ancient Coin Classification Using Reverse Motif Recognition: Image-based classification of Roman Republican coins. BibRef

Candemir, S.[Sema], Borovikov, E.[Eugene], Santosh, K.C., Antani, S.[Sameer], Thoma, G.[George],
RSILC: Rotation- and Scale-Invariant, Line-based Color-aware descriptor,
IVC(42), No. 1, 2015, pp. 1-12.
Elsevier DOI 1509
Image descriptor BibRef

Liang, C.[Chao], Yang, W.M.[Wen-Ming], Zhou, F.[Fei], Liao, Q.M.[Qing-Min],
Reflection and Rotation Invariant Uniform Patterns for Texture Classification,
IEICE(E99-D), No. 5, May 2016, pp. 1400-1403.
WWW Link. 1605
BibRef

Liang, C.[Chao], Yang, W.M.[Wen-Ming], Zhou, F.[Fei], Liao, Q.M.[Qing-Min],
RBM-LBP: Joint Distribution of Multiple Local Binary Patterns for Texture Classification,
IEICE(E99-D), No. 11, November 2016, pp. 2828-2831.
WWW Link. 1611
BibRef

Zhao, W.T.[Wen-Teng], Lu, Z.Q.[Zong-Qing], Liao, Q.M.[Qing-Min],
Texture classification using uniform rotation invariant gradient,
ICIP15(3650-3654)
IEEE DOI 1512
local descriptor BibRef

Yu, L.L.[Ling-Li], Zhou, K.J.[Kai-Jun], Yang, Y.L.[Yong-Liang], Chen, H.C.[Hai-Chu],
Bionic RSTN invariant feature extraction method for image recognition and its application,
IET-IPR(11), No. 4, April 2017, pp. 227-236.
DOI Link 1704
RSTN: rotation, scaling, translation, and noise invariant features. BibRef

Yang, Y.[Yi], Duan, F.J.[Fa-Jie], Ma, L.[Ling], Jiang, J.J.[Jia-Jia],
A Robust method for constructing rotational invariant descriptors,
SP:IC(60), No. 1, 2018, pp. 224-236.
Elsevier DOI 1712
Multi-neighborhood BibRef

Yang, Y.[Yi], Duan, F.J.[Fa-Jie], Ma, L.[Ling],
A rotationally invariant descriptor based on mixed intensity feature histograms,
PR(76), No. 1, 2018, pp. 162-174.
Elsevier DOI 1801
Rotation invariant BibRef

Feraidooni, M.M.[Mohammad Mahdi], Gharavian, D.[Davood],
A new approach for rotation-invariant and noise-resistant texture analysis and classification,
MVA(29), No. 3, April 2018, pp. 455-466.
WWW Link. 1804
BibRef

Roy, S.K.[Swalpa Kumar], Chanda, B.[Bhabatosh], Chaudhuri, B.B.[Bidyut B.], Banerjee, S.[Soumitro], Ghosh, D.K.[Dipak Kumar], Dubey, S.R.[Shiv Ram],
Local directional ZigZag pattern: A rotation invariant descriptor for texture classification,
PRL(108), 2018, pp. 23-30.
Elsevier DOI 1805
Local ZigZag Pattern (), Local Directional ZigZag Pattern (), Rotation invariance, Texture classification BibRef

Sadeghi, B.[Bahman], Jamshidi, K.[Kamal], Vafaei, A.[Abbas], Monadjemi, S.A.[S. Amirhassan],
2DIGH: a polar invariant local image descriptor based on joint histogram,
VC(34), No. 11, November 2018, pp. 1579-1595.
Springer DOI 1810
BibRef

Kitagawa, M.[Masamichi], Shimizu, I.[Ikuko],
Memory Saving Feature Descriptor Using Scale and Rotation Invariant Patches around the Feature Ppoints,
IEICE(E102-D), No. 5, May 2019, pp. 1106-1110.
WWW Link. 1906
For phones and tablets. Compare to ORB, BRISK, AKAZE. BibRef

Zhang, D.B.[Dong-Bo], Chen, H.L.[Hong-Lei], Yin, F.[Feng], Chen, Z.Q.A.[Zhi-Qi-Ang], Tang, H.Z.[Hong-Zhong], Xu, H.X.[Hai-Xia],
Efficient and distinctive binary descriptor for rotated circular image recognition,
MVA(30), No. 4, June 2019, pp. 749-761.
Springer DOI 1906
BibRef

Jiang, R., Mei, S., Ma, M., Zhang, S.,
Rotation-Invariant Feature Learning in VHR Optical Remote Sensing Images via Nested Siamese Structure With Double Center Loss,
GeoRS(59), No. 4, April 2021, pp. 3326-3337.
IEEE DOI 2104
Feature extraction, Training, Remote sensing, Optical imaging, Optical sensors, Object detection, Task analysis, rotation-invariant BibRef

You, Y.[Yang], Lou, Y.J.[Yu-Jing], Shi, R.X.[Ruo-Xi], Liu, Q.[Qi], Tai, Y.W.[Yu-Wing], Ma, L.Z.[Li-Zhuang], Wang, W.M.[Wei-Ming], Lu, C.[Cewu],
PRIN/SPRIN: On Extracting Point-Wise Rotation Invariant Features,
PAMI(44), No. 12, December 2022, pp. 9489-9502.
IEEE DOI 2212
Feature extraction, Convolution, Shape, Recurrent neural networks, Task analysis, Solid modeling, Point cloud, object analysis, feature learning BibRef

Wei, C.Y.[Chong-Yang], Ni, W.P.[Wei-Ping], Qin, Y.[Yao], Wu, J.Z.[Jun-Zheng], Zhang, H.[Han], Liu, Q.[Qiang], Cheng, K.[Kenan], Bian, H.[Hui],
RiDOP: A Rotation-Invariant Detector with Simple Oriented Proposals in Remote Sensing Images,
RS(15), No. 3, 2023, pp. xx-yy.
DOI Link 2302
BibRef


x Lee, J.[Jongmin], Kim, B.[Byungjin], Kim, S.[Seungwook], Cho, M.[Minsu],
Learning Rotation-Equivariant Features for Visual Correspondence,
CVPR23(21887-21897)
IEEE DOI 2309
BibRef

Bagad, P.[Piyush], Eijkelboom, F.[Floor], Fokkema, M.[Mark], de Goede, D.[Danilo], Hilders, P.[Paul], Kofinas, M.[Miltiadis],
C-3PO: Towards Rotation Equivariant Feature Detection and Description,
VIPriors22(694-705).
Springer DOI 2304
BibRef

Lu, S.Y.[Sheng-Yu], Mahmoodi, S.[Sasan], Niranjan, M.[Mahesan],
Robust 3D rotation invariant local binary pattern for volumetric texture classification,
ICPR22(578-584)
IEEE DOI 2212
Solid modeling, Image segmentation, Lighting, Solids, Information filters, Robustness, texture descriptors BibRef

Soleimani, P.[Parastoo], Li, K.F.[Kin Fun], Capson, D.W.[David W.],
A circular shifting binary descriptor for efficient rotation invariant image matching,
ICPR22(393-399)
IEEE DOI 2212
Image matching, Estimation, Hardware, Tuning BibRef

Mehr, É.[Éloi], Lieutier, A.[André], Bermudez, F.S.[Fernando Sanchez], Guitteny, V.[Vincent], Thome, N.[Nicolas], Cord, M.[Matthieu],
Manifold Learning in Quotient Spaces,
CVPR18(9165-9174)
IEEE DOI 1812
Geometry, not orientation. Shape, Geometry, Space vehicles, Manifolds, Orbits, Solid modeling BibRef

Yang, B., Chen, X., Zhang, Y.,
Flexible Rotation Invariant Bases from Orthogonal Moments,
ICPR18(1548-1553)
IEEE DOI 1812
Distortion, Numerical stability, Phase change materials, Pattern recognition, Automation, Indexes, Measurement, rotation moment invariants BibRef

Deng, H.W.[Hao-Wen], Birdal, T.[Tolga], Ilic, S.[Slobodan],
PPF-FoldNet: Unsupervised Learning of Rotation Invariant 3D Local Descriptors,
ECCV18(VI: 620-638).
Springer DOI 1810
BibRef

Zhang, X., Liu, L., Xie, Y., Chen, J., Wu, L., Pietikäinen, M.,
Rotation Invariant Local Binary Convolution Neural Networks,
CEFR-LCV17(1210-1219)
IEEE DOI 1802
Active filters, Computer architecture, Convolution, Image coding, Neural networks BibRef

El Rhabi, Y.[Youssef], Simon, L.[Loic], Brun, L.[Luc], Canet, J.L.[Josep Llados], Lumbreras, F.[Felipe],
Information Theoretic Rotationwise Robust Binary Descriptor Learning,
SSSPR16(368-378).
Springer DOI 1611

See also BOLD: Binary online learned descriptor for efficient image matching. BibRef

Zuo, C.L.[Cheng-Lin], Jovanov, L.[Ljubomir], Luong, H.Q.[Hiep Quang], Goossens, B.[Bart], Philips, W.[Wilfried], Liu, Y.[Yu], Zhang, M.J.[Mao-Jun],
Rotation invariant similarity measure for non-local self-similarity based image denoising,
ICIP15(1618-1622)
IEEE DOI 1512
Image denoising; non-local means; rotation invariant; similarity measure BibRef

Sharma, M.[Monika], Ghosh, H.[Hiranmay],
Histogram of gradient magnitudes: A rotation invariant texture-descriptor,
ICIP15(4614-4618)
IEEE DOI 1512
Image classification BibRef

Akhoury, S.S.[Sharat Saurabh], Laganière, R.[Robert],
Training Binary Descriptors for Improved Robustness and Efficiency in Real-Time Matching,
CIAP13(II:288-298).
Springer DOI 1309
Keypoint extration. Allow scale and rotation sensitivity. BibRef

Schmidt, U.[Uwe], Roth, S.[Stefan],
Learning rotation-aware features: From invariant priors to equivariant descriptors,
CVPR12(2050-2057).
IEEE DOI 1208
BibRef

Taquet, M.[Maxime], Jacques, L.[Laurent], Macq, B.[Benoit], Jaume, S.[Sylvain],
Compact rotation invariant image descriptors by spectral trimming,
ICIP11(2033-2036).
IEEE DOI 1201
BibRef

Yue, S.C.[Si-Cong], Wang, Q.[Qing], Zhao, R.C.[Rong-Chun],
Feature Points Detection Using Combined Character Along Principal Orientation,
MIRAGE07(128-138).
Springer DOI 0703
BibRef

Szumilas, L.[Lech], Donner, R.[Rene], Langs, G.[Georg], Hanbury, A.[Allan],
Local Structure Detection with Orientation-invariant Radial Configuration,
CVPR07(1-7).
IEEE DOI 0706
Feature, interest points. BibRef

Chapter on 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture continues in
Scale Invariant Features, SIFT, SURF, ASIFT .


Last update:Mar 16, 2024 at 20:36:19