7.1.8.1 Keypoint Detection

Chapter Contents (Back)
Interest Points. Key Points. More general: See also Interest Operators, Interest Points, Feature Points, Salient Points.

Li, J.[Jing], Yang, T.[Tao], Pan, Q.[Quan], Cheng, Y.M.[Yong-Mei], Hou, J.[Jun],
A Novel Algorithm For Speeding Up Keypoint Detection And Matching,
IJIG(8), No. 4, October 2008, pp. 643-661. 0804
BibRef

Mishra, A.K.[Akshaya K.], Wong, A.[Alexander], Clausi, D.A.[David A.], Fieguth, P.W.[Paul W.],
Quasi-random nonlinear scale space,
PRL(31), No. 13, 1 October 2010, pp. 1850-1859.
Elsevier DOI 1003
BibRef
Earlier: A2, A1, A3, A4:
Quasi-Random Scale Space Approach to Robust Keypoint Extraction in High-Noise Environments,
CRV10(25-31).
IEEE DOI 1005
Nonlinear scale space; Bayesian estimation; Quasi-random; Anisotropic diffusion; Multi-scale; Edge detection BibRef

Mishra, A.K.[Akshaya K.], Wong, A.[Alexander], Fieguth, P.W.[Paul W.], Clausi, D.A.[David A.],
Multi-scale 3D representation via volumetric quasi-random scale space,
ICIP11(2105-2108).
IEEE DOI 1201
BibRef

Park, U., Park, J., Jain, A.K.,
Robust Keypoint Detection Using Higher-Order Scale Space Derivatives: Application to Image Retrieval,
SPLetters(21), No. 8, August 2014, pp. 962-965.
IEEE DOI 1406
Accuracy BibRef

Tian, T., Sethi, I., Ming, D., Patel, N.,
A Zoned Image Patch Permutation Descriptor,
SPLetters(22), No. 6, June 2015, pp. 728-732.
IEEE DOI 1411
oFAST for keypoints with orientations, then patterns applied within the local keypoint patch. BibRef

Yu, X., Yang, J., Wang, T., Huang, T.,
Key Point Detection by Max Pooling for Tracking,
Cyber(45), No. 3, March 2015, pp. 444-452.
IEEE DOI 1502
Cybernetics BibRef

Yu, X., Yang, J., Lin, Z., Wang, J., Wang, T., Huang, T.,
Subcategory-Aware Object Detection,
SPLetters(22), No. 9, September 2015, pp. 1472-1476.
IEEE DOI 1503
Clustering algorithms BibRef

Buoncompagni, S.[Simone], Maio, D.[Dario], Maltoni, D.[Davide], Papi, S.[Serena],
Saliency-based keypoint selection for fast object detection and matching,
PRL(62), No. 1, 2015, pp. 32-40.
Elsevier DOI 1507
Feature selection BibRef

Zhu, J.K.[Jian-Ke], Wu, C.X.[Chen-Xia], Chen, C.[Chun], Cai, D.[Deng],
Treelets Binary Feature Retrieval for Fast Keypoint Recognition,
Cyber(45), No. 10, October 2015, pp. 2129-2141.
IEEE DOI 1509
Computed tomography BibRef

Wu, C.X.[Chen-Xia], Zhu, J.K.[Jian-Ke], Zhang, J.[Jiemi], Chen, C.[Chun], Cai, D.[Deng],
A Convolutional Treelets Binary Feature Approach to Fast Keypoint Recognition,
ECCV12(V: 368-382).
Springer DOI 1210
BibRef

Theodosiou, Z.[Zenonas],
Image Retrieval: Modelling Keywords via Low-level Features,
ELCVIA(14), No. 3, 2015, pp. xx-yy.
DOI Link 1601
Thesis summary. BibRef

Theodosiou, Z., Tsapatsoulis, N.,
Spatial histogram of keypoints (SHIK),
ICIP13(2924-2928)
IEEE DOI 1402
Hilbert space-filling curve BibRef

Tsai, C.Y., Huang, C.H., Tsao, A.H.,
Graphics processing unit-accelerated multi-resolution exhaustive search algorithm for real-time keypoint descriptor matching in high-dimensional spaces,
IET-CV(10), No. 3, 2016, pp. 212-219.
DOI Link 1604
feature extraction. GPU implementation. BibRef

Karpushin, M.[Maxim], Valenzise, G.[Giuseppe], Dufaux, F.[Frederic],
Keypoint Detection in RGBD Images Based on an Anisotropic Scale Space,
MultMed(18), No. 9, September 2016, pp. 1762-1771.
IEEE DOI 1609
BibRef
Earlier:
Improving distinctiveness of brisk features using depth maps,
ICIP15(2399-2403)
IEEE DOI 1512
feature extraction. BRISK; RGBD features; binary descriptor; distinctiveness; texture+depth BibRef

Rey-Otero, I.[Ives], Morel, J.M.[Jean-Michel], Delbracio, M.[Mauricio],
An Analysis of the Factors Affecting Keypoint Stability in Scale-Space,
JMIV(56), No. 3, November 2016, pp. 554-572.
Springer DOI 1609
BibRef

Lomeli-Rodriguez, J.[Jaime], Nixon, M.S.[Mark S.],
An extension to the brightness clustering transform and locally contrasting keypoints,
MVA(27), No. 8, November 2016, pp. 1187-1196.
Springer DOI 1612
BibRef
Earlier:
The Brightness Clustering Transformand Locally Contrasting Keypoints,
CAIP15(I:362-373).
Springer DOI 1511
BibRef

Royer, E.[Emilien], Lelore, T.[Thibault], Bouchara, F.[Frédéric],
COnfusion REduction (CORE) algorithm for local descriptors, floating-point and binary cases,
CVIU(158), No. 1, 2017, pp. 115-125.
Elsevier DOI 1704
Keypoints filtering BibRef

Matusiak, K.[Karol], Skulimowski, P.[Piotr], Strumillo, P.[Pawel],
Unbiased evaluation of keypoint detectors with respect to rotation invariance,
IET-CV(11), No. 7, October 2017, pp. 507-516.
DOI Link 1709
BibRef


Markuš, N.[Nenad], Pandžic, I.S.[Igor S.], Ahlberg, J.[Jörgen],
Learning local descriptors by optimizing the keypoint-correspondence criterion,
ICPR16(2380-2385)
IEEE DOI 1705
Computer architecture, Computer vision, Mathematical model, Neural networks, Standards, Three-dimensional displays, Training BibRef

Chatoux, H.[Hermine], Lecellier, F.[François], Fernandez-Maloigne, C.[Christine],
Comparative study of descriptors with dense key points,
ICPR16(1988-1993)
IEEE DOI 1705
Detectors, Histograms, Latches, Lighting, Protocols, Retina, Shearing BibRef

Olson, C.F.[Clark F.], Hoover, S.A.[Sam A.], Soltman, J.L.[Jordan L.], Zhang, S.[Siqi],
Complementary Keypoint Descriptors,
ISVC16(I: 341-352).
Springer DOI 1701
BibRef

Olson, C.F.[Clark F.], Zhang, S.Q.[Si-Qi],
Keypoint Recognition with Histograms of Normalized Colors,
CRV16(311-318)
IEEE DOI 1612
color; descriptor; keypoint; object recognition BibRef

St-Charles, P.L.[Pierre-Luc], Bilodeau, G.A.[Guillaume-Alexandre], Bergevin, R.[Robert],
Fast Image Gradients Using Binary Feature Convolutions,
Robust16(1074-1082)
IEEE DOI 1612
BibRef

Okutani, R., Sugimoto, K., Kamata, S.I.,
Efficient keypoint detection and description using filter kernel decomposition in scale space,
ICIP16(31-35)
IEEE DOI 1610
Computational complexity BibRef

Araujo, A., Lakshman, H., Angst, R., Girod, B.,
Modeling the impact of keypoint detection errors on local descriptor similarity,
ICIP16(305-309)
IEEE DOI 1610
Closed-form solutions BibRef

Yi, K.M.[Kwang Moo], Trulls, E.[Eduard], Lepetit, V.[Vincent], Fua, P.[Pascal],
LIFT: Learned Invariant Feature Transform,
ECCV16(VI: 467-483).
Springer DOI 1611
BibRef

Yi, K.M.[Kwang Moo], Verdie, Y.[Yannick], Fua, P.[Pascal], Lepetit, V.[Vincent],
Learning to Assign Orientations to Feature Points,
CVPR16(107-116)
IEEE DOI 1612
BibRef
Earlier: A2, A1, A3, A4:
TILDE: A Temporally Invariant Learned DEtector,
CVPR15(5279-5288)
IEEE DOI 1510
detect repeatable keypoints. BibRef

Danielsson, O.[Oscar],
Category-Sensitive Hashing and Bloom Filter Based Descriptors for Online Keypoint Recognition,
SCIA15(329-340).
Springer DOI 1506
BibRef

Gadelha, M.A.[Matheus A.], Carvalho, B.M.[Bruno M.],
DRINK: Discrete Robust Invariant Keypoints,
ICPR14(821-826)
IEEE DOI 1412
Brightness BibRef

Lee, S.[Suwon], Lee, S.W.[Sang-Wook], Chae, Y.N.[Yeong Nam], Yang, H.S.[Hyun S.],
Lightweight Random Ferns using binary representation,
ICPR12(1342-1345).
WWW Link. 1302
real-time keypoint recognition BibRef

Fragoso, V.[Victor], Turk, M.[Matthew], Hespanha, J.[Joao],
Locating binary features for keypoint recognition using noncooperative games,
ICIP12(2389-2392).
IEEE DOI 1302
BibRef

Martins, P.[Pedro], Carvalho, P.[Paulo], Gatta, C.[Carlo],
Stable Salient Shapes,
DICTA12(1-8).
IEEE DOI 1303
BibRef
And:
Context Aware Keypoint Extraction for Robust Image Representation,
BMVC12(100).
DOI Link 1301
BibRef

Alahi, A.[Alexandre], Ortiz, R.[Raphael], Vandergheynst, P.[Pierre],
FREAK: Fast Retina Keypoint,
CVPR12(510-517).
IEEE DOI 1208
vs. SIFT, SURF BibRef

Gauglitz, S.[Steffen], Turk, M.A.[Matthew A.], Höllerer, T.[Tobias],
Improving Keypoint Orientation Assignment,
BMVC11(xx-yy).
HTML Version. 1110
BibRef

Ventura, J.[Jonathan], Hollerer, T.[Tobias],
Fast and scalable keypoint recognition and image retrieval using binary codes,
WMVC11(697-702).
IEEE DOI 1101
BibRef

Rudinac, M.[Maja], Lenseigne, B.[Boris], Jonker, P.P.[Pieter P.],
Keypoint Extraction and Selection for Object Recognition,
MVA09(191-).
PDF File. 0905
BibRef

Marimon, D.[David], Bonnin, A.[Arturo], Adamek, T.[Tomasz], Gimeno, R.[Roger],
DARTs: Efficient scale-space extraction of DAISY keypoints,
CVPR10(2416-2423).
IEEE DOI 1006
See also Picking the best DAISY. BibRef

Jamshy, S.[Shahar], Krupka, E.[Eyal], Yeshurun, Y.[Yehezkel],
Reducing Keypoint Database Size,
CIAP09(113-122).
Springer DOI 0909
BibRef

Strecha, C.[Christoph], Lindner, A.[Albrecht], Ali, K.[Karim], Fua, P.[Pascal],
Training for Task Specific Keypoint Detection,
DAGM09(151-160).
Springer DOI 0909
Train interest point detector for only the task specific ones. BibRef

Herpers, R., Sommer, G., Michaelis, M., Witta, L.,
Context Based Detection of Keypoints and Features in Eye Regions,
ICPR96(II: 23-28).
IEEE DOI 9608
(GSF, D) BibRef

Chapter on 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture continues in
HOG Analysis, Histogram of Oriented Gradient .


Last update:Nov 18, 2017 at 20:56:18