7.1.10.6 Scale Invariant Features, SIFT, SURF, ASIFT

Chapter Contents (Back)
Interest Points. Salient Points. Feature Points. SIFT. ASIFT. SURF.
See also Interest Operators, Interest Points, Feature Points, Salient Points. Of course you want to see:
See also Distinctive Image Features from Scale-Invariant Keypoints.

Fayolle, J.[Jacques], Riou, L.[Laurence], Ducottet, C.[Christophe],
Robustness of a multiscale scheme of feature points detection,
PR(33), No. 9, September 2000, pp. 1437-1453.
Elsevier DOI 0005
BibRef

Fayolle, J., Ducottet, C., Riou, L., Coudert, S.,
A Wavelet Based Multiscale Detection Scheme of Feature Points,
ICPR00(Vol III: 421-424).
IEEE DOI 0009
BibRef

Mikolajczyk, K.[Krystian], Schmid, C.[Cordelia],
Scale and Affine Invariant Interest Point Detectors,
IJCV(60), No. 1, October 2004, pp. 63-86.
DOI Link 0405
BibRef
Earlier:
An Affine Invariant Interest Point Detector,
ECCV02(I: 128 ff.).
Springer DOI 0205

See also Comparison of Affine Region Detectors, A. BibRef

Mikolajczyk, K.[Krystian],
Detection of local features invariant to affine transformations,
Ph.D.Thesis, Institut National Polytechnique de Grenoble, France, 2002. BibRef 0200

Mikolajczyk, K.[Krystian], Schmid, C.[Cordelia],
Indexing Based on Scale Invariant Interest Points,
ICCV01(I: 525-531).
IEEE DOI 0106
Interest point computation. BibRef

Mikolajczyk, K., Zisserman, A., Schmid, C.,
Shape recognition with edge-based features,
BMVC03(xx-yy).
HTML Version. 0409
BibRef

Koniusz, P.[Piotr], Mikolajczyk, K.[Krystian],
Soft assignment of visual words as Linear Coordinate Coding and optimisation of its reconstruction error,
ICIP11(2413-2416).
IEEE DOI 1201
BibRef
And:
Spatial Coordinate Coding to reduce histogram representations, Dominant Angle and Colour Pyramid Match,
ICIP11(661-664).
IEEE DOI 1201
BibRef
Earlier:
On a Quest for Image Descriptors Based on Unsupervised Segmentation Maps,
ICPR10(762-765).
IEEE DOI 1008
BibRef
Earlier:
Segmentation Based Interest Points and Evaluation of Unsupervised Image Segmentation Methods,
BMVC09(xx-yy).
PDF File. 0909
BibRef

Bay, H.[Herbert], Ess, A.[Andreas], Tuytelaars, T.[Tinne], Van Gool, L.J.[Luc J.],
Speeded-Up Robust Features (SURF),
CVIU(110), No. 3, June 2008, pp. 346-359.
Elsevier DOI 0711
Award, CVIU, Most Cited. (2008-2010) BibRef
Earlier: A1, A3, A4, Only:
SURF: Speeded Up Robust Features,
ECCV06(I: 404-417).
Springer DOI 0608
Award, Koenderink Prize. Interest points; Local features; Feature description; Camera calibration; Object recognition. Use essential parts of features to simplify for speed.
See also Comparison of Affine Region Detectors, A. BibRef

Tuytelaars, T.[Tinne],
Dense interest points,
CVPR10(2281-2288).
IEEE DOI 1006
BibRef

Willems, G.[Geert], Tuytelaars, T.[Tinne], Van Gool, L.J.[Luc J.],
An Efficient Dense and Scale-Invariant Spatio-Temporal Interest Point Detector,
ECCV08(II: 650-663).
Springer DOI 0810
BibRef

Carneiro, G.[Gustavo], Jepson, A.D.[Allan D.],
Flexible Spatial Configuration of Local Image Features,
PAMI(29), No. 12, December 2007, pp. 2089-2104.
IEEE DOI 0711
BibRef
Earlier:
The Distinctiveness, Detectability, and Robustness of Local Image Features,
CVPR05(II: 296-301).
IEEE DOI 0507
BibRef
Earlier:
Flexible spatial models for grouping local image features,
CVPR04(II: 747-754).
IEEE DOI 0408
BibRef
Earlier:
Phase-Based Local Features,
ECCV02(I: 282 ff.).
Springer DOI 0205
Local features are intended to be reliable under various transformations, but this is not always the case. Introduce two geometric filters, based on semilocal spatial configuration of local features robust to rigid and non-rigid transformations. BibRef

Carneiro, G., Jepson, A.D.,
Pruning local feature correspondences using shape context,
ICPR04(III: 16-19).
IEEE DOI 0409
BibRef
Earlier:
Multi-scale phase-based local features,
CVPR03(I: 736-743).
IEEE DOI 0307
Where: interest point location; What: feature detection. Quantitative evaluation of both the where and the what for a) phase-based local features (Carneiro and Jepson, 2002),
See also Flexible Spatial Configuration of Local Image Features. b) differential invariants (Schmid and Mohr, 1997),
See also Local Grayvalue Invariants for Image Retrieval. c) the scale invariant feature transform (SIFT) (Lowe, 1999).
See also Distinctive Image Features from Scale-Invariant Keypoints. The first comes out best. BibRef

Carneiro, G.[Gustavo],
The automatic design of feature spaces for local image descriptors using an ensemble of non-linear feature extractors,
CVPR10(3509-3516).
IEEE DOI Video of talk:
WWW Link. 1006
BibRef

Carneiro, G.[Gustavo], Lowe, D.G.[David G.],
Sparse Flexible Models of Local Features,
ECCV06(III: 29-43).
Springer DOI 0608
BibRef

Carneiro, G.[Gustavo], Jepson, A.D.[Allan D.],
The quantitative characterization of the distinctiveness and robustness of local image descriptors,
IVC(27), No. 8, 2 July 2009, pp. 1143-1156.
Elsevier DOI 0906
Visual object recognition; Local image descriptors; Discriminant classifier; Regression models BibRef

Mukherjee, A., Velez-Reyes, M., Roysam, B.,
Interest Points for Hyperspectral Image Data,
GeoRS(47), No. 3, March 2009, pp. 748-760.
IEEE DOI 0903
BibRef

Dorado-Munoz, L.P., Velez-Reyes, M., Mukherjee, A., Roysam, B.,
A Vector SIFT Detector for Interest Point Detection in Hyperspectral Imagery,
GeoRS(50), No. 11, November 2012, pp. 4521-4533.
IEEE DOI 1210
BibRef

Li, C.L.[Can-Lin], Ma, L.Z.[Li-Zhuang],
A new framework for feature descriptor based on SIFT,
PRL(30), No. 5, 1 April 2009, pp. 544-557.
Elsevier DOI 0903
Feature descriptor; SIFT; Distinctiveness; Invariance; Elliptical neighboring region; Log-polar histogram BibRef

Cheung, W., Hamarneh, G.[Ghassan],
n-SIFT: n-Dimensional Scale Invariant Feature Transform,
IP(18), No. 9, September 2009, pp. 2012-2021.
IEEE DOI 0909
BibRef

Kawewong, A.[Aram], Tangruamsub, S.[Sirinart], Hasegawa, O.[Osamu],
Position-Invariant Robust Features for Long-Term Recognition of Dynamic Outdoor Scenes,
IEICE(E93-D), No. 9, September 2010, pp. 2587-2601.
WWW Link. 1003
BibRef
Earlier:
Wide-Baseline Visible Features for Highly Dynamic Scene Recognition,
CAIP09(723-731).
Springer DOI 0909
Find features (SIFT, SURF) that are widely visible. BibRef

Ai, D.N.[Dan-Ni], Han, X.H.[Xian-Hua], Ruan, X.[Xiang], Chen, Y.W.[Yen-Wei],
Color Independent Components Based SIFT Descriptors for Object/Scene Classification,
IEICE(E93-D), No. 9, September 2010, pp. 2577-2586.
WWW Link. 1003
BibRef
And:
Adaptive Color Independent Components Based SIFT Descriptors for Image Classification,
ICPR10(2436-2439).
IEEE DOI 1008
BibRef

Ai, D.N.[Dan-Ni], Han, X.H.[Xian-Hua], Duan, G.F.[Gui-Fang], Ruan, X.[Xiang], Chen, Y.W.[Yen-Wei],
Global Selection vs Local Ordering of Color SIFT Independent Components for Object/Scene Classification,
IEICE(E94-D), No. 9, September 2011, pp. 1800-1808.
WWW Link. 1110
BibRef

Gao, J.[Jian], Huang, X.H.[Xin-Han], Liu, B.[Bo],
A quick scale-invariant interest point detecting approach,
MVA(21), No. 3, April 2010, pp. xx-yy.
Springer DOI 1003
BibRef

Cui, C.H.[Chun-Hui], Ngan, K.N.[King Ngi],
Scale- and Affine-Invariant Fan Feature,
IP(20), No. 6, June 2011, pp. 1627-1640.
IEEE DOI 1106
Dealing with surface boundaries. BibRef

Cui, C.H.[Chun-Hui], Ngan, K.N.[King Ngi],
Global Propagation of Affine Invariant Features for Robust Matching,
IP(22), No. 7, 2013, pp. 2876-2888.
IEEE DOI 1307
filtering theory; rendering (computer graphics); affine invariant features; image based rendering; nonrigid deformation BibRef

Dickscheid, T.[Timo], Schindler, F.[Falko], Förstner, W.[Wolfgang],
Coding Images with Local Features,
IJCV(94), No. 2, September 2011, pp. 154-174.
WWW Link. 1101
BibRef
Earlier: A3, A1, A2:
Detecting interpretable and accurate scale-invariant keypoints,
ICCV09(2256-2263).
IEEE DOI 0909
Describing images with local features, consider in terms usually used for coding. Junction type features, scale space version of Forstner detector (
See also Framework For Low Level Feature Extraction, A. ), and spiral feature of Bigun (
See also Structure Feature for Image Processing Applications Based on Spiral Functions, A. ). BibRef

Schindler, F.[Falko], Förstner, W.[Wolfgang],
DijkstraFPS: Graph Partitioning in Geometry and Image Processing,
PFG(2013), No. 4, 2013, pp. 285-296.
DOI Link 1309
BibRef

Roscher, R.[Ribana], Schindler, F.[Falko], Förstner, W.[Wolfgang],
High Dimensional Correspondences from Low Dimensional Manifolds: An Empirical Comparison of Graph-Based Dimensionality Reduction Algorithms,
Subspace10(334-343).
Springer DOI 1109
correspondence on lower dimensional space. BibRef

Olague, G.[Gustavo], Trujillo, L.[Leonardo],
Evolutionary-computer-assisted design of image operators that detect interest points using genetic programming,
IVC(29), No. 7, June 2011, pp. 484-498.
Elsevier DOI 1101
BibRef
Earlier: A2, A1:
Scale Invariance for Evolved Interest Operators,
EvoIASP07(423-430).
Springer DOI 0704
BibRef
Earlier: A2, A1:
Using Evolution to Learn How to Perform Interest Point Detection,
ICPR06(I: 211-214).
IEEE DOI 0609
Interest points; Computer assisted design; Evolutionary computation; Genetic programming; Evolutionary computer vision BibRef

Trujillo, L.[Leonardo], Olague, G.[Gustavo], Fernandez, F., Lutton, E.,
Evolutionary feature selection for probabilistic object recognition, novel object detection and object saliency estimation using GMMs,
BMVC07(xx-yy).
PDF File. 0709
BibRef

Bradley, P., Jutzi, B.,
Improved Feature Detection in Fused Intensity-Range Images with Complex SIFT (CSIFT),
RS(3), No. 9, September 2011, pp. 2076-2088.
DOI Link 1203
BibRef

Sadek, R., Constantinopoulos, C., Meinhardt, E., Ballester, C., Caselles, V.,
On Affine Invariant Descriptors Related to SIFT,
SIIMS(5), No. 2, 2012, pp. 652-687.
DOI Link 1206
BibRef

Chang, L.[Leonardo], Hernández-Palancar, J.[José], Sucar, L.E.[L. Enrique], Arias-Estrada, M.[Miguel],
FPGA-based detection of SIFT interest keypoints,
MVA(24), No. 2, February 2013, pp. 371-392.
WWW Link. 1302
BibRef

Park, H.[Hanhoon], Mitsumine, H.[Hideki], Fujii, M.[Mahito],
Fast Detection of Robust Features by Reducing the Number of Box Filtering in SURF,
IEICE(E94-D), No. 3, March 2011, pp. 725-728.
WWW Link. 1103
BibRef

Chi, Y.[Yitao], Xiong, Z.[Zhang], Chang, Q.[Qing], Li, C.[Chao], Sheng, H.[Hao],
Improving Hessian Matrix Detector for SURF,
IEICE(E94-D), No. 4, April 2011, pp. 921-925.
WWW Link. 1104
BibRef

Liao, C.[Chao], Wang, G.J.[Gui-Jin], Miao, Q.[Quan], Wang, Z.G.[Zhi-Guo], Shi, C.B.[Chen-Bo], Lin, X.G.[Xing-Gang],
DSP-Based Parallel Implementation of Speeded-Up Robust Features,
IEICE(E94-D), No. 4, April 2011, pp. 930-933.
WWW Link. 1104
SURF BibRef

Ehsan, S.[Shoaib], Kanwal, N.[Nadia], Clark, A.F.[Adrian F.], McDonald-Maier, K.D.[Klaus D.],
An Algorithm for the Contextual Adaption of SURF Octave Selection With Good Matching Performance: Best Octaves,
IP(21), No. 1, January 2012, pp. 297-304.
IEEE DOI 1112
BibRef
Earlier:
Measuring the Coverage of Interest Point Detectors,
ICIAR11(I: 253-261).
Springer DOI 1106
BibRef

Kanwal, N.[Nadia], Ehsan, S.[Shoaib], Clark, A.F.[Adrian F.],
Are Performance Differences of Interest Operators Statistically Significant?,
CAIP11(II: 429-436).
Springer DOI 1109
Evaluation, Interest Points. BibRef

Alcantarilla, P.F.[Pablo F.], Bergasa, L.M.[Luis M.], Davison, A.J.[Andrew J.],
Gauge-SURF descriptors,
IVC(31), No. 1, January 2013, pp. 103-116.
Elsevier DOI 1302
Gauge coordinates; Scale space; Feature descriptors; Integral image BibRef

Alcantarilla, P.F.[Pablo Fernández], Bartoli, A.E.[Adrien E.], Davison, A.J.[Andrew J.],
KAZE Features,
ECCV12(VI: 214-227).
Springer DOI 1210
BibRef

Alcantarilla, P.F.[Pablo F.], Nuevo, J.[Jesus], Bartoli, A.E.[Adrien E.],
Fast Explicit Diffusion for Accelerated Features in Nonlinear Scale Spaces,
BMVC13(xx-yy).
DOI Link 1402
BibRef

Jing, H.[Huiyun], He, X.[Xin], Han, Q.[Qi], Niu, X.[Xiamu],
CBRISK: Colored Binary Robust Invariant Scalable Keypoints,
IEICE(E96-D), No. 2, February 2013, pp. 392-395.
WWW Link. 1301
BRISK faster than SIFT/SURF. Extend BRISK to include color information.
See also BRISK: Binary Robust invariant scalable keypoints. BibRef

Chiu, L.C.[Liang-Chi], Chang, T.S.[Tian-Sheuan], Chen, J.Y.[Jiun-Yen], Chang, N.Y.C.,
Fast SIFT Design for Real-Time Visual Feature Extraction,
IP(22), No. 8, 2013, pp. 3158-3167.
IEEE DOI 1307
CMOS integrated circuits; fast SIFT design; BibRef

Han, H.[Hong], Han, Q.Q.[Qi-Qiang], Li, X.J.[Xiao-Jun], Gu, J.Y.[Jian-Yin],
Hierarchical spatial pyramid max pooling based on SIFT features and sparse coding for image classification,
IET-CV(7), No. 2, 2013, pp. 144-150.
DOI Link 1307
BibRef

Sima, A.A.[Aleksandra A.], Buckley, S.J.[Simon J.],
Optimizing SIFT for Matching of Short Wave Infrared and Visible Wavelength Images,
RS(5), No. 5, 2013, pp. 2037-2056.
DOI Link 1307
BibRef

Liao, K.Y.[Kai-Yang], Liu, G.Z.[Gui-Zhong], Hui, Y.S.[You-Shi],
An improvement to the SIFT descriptor for image representation and matching,
PRL(34), No. 11, 1 August 2013, pp. 1211-1220.
Elsevier DOI 1306
Local descriptor; SIFT; Point matching BibRef

Mainali, P.[Pradip], Lafruit, G.[Gauthier], Yang, Q.[Qiong], Geelen, B.[Bert], Van Gool, L.J.[Luc J.], Lauwereins, R.[Rudy],
SIFER: Scale-Invariant Feature Detector with Error Resilience,
IJCV(104), No. 2, September 2013, pp. 172-197.
Springer DOI 1308

See also Robust Low Complexity Corner Detector. BibRef

Mainali, P.[Pradip], Lafruit, G.[Gauthier], Tack, K., Van Gool, L.J.[Luc J.], Lauwereins, R.[Rudy],
Derivative-Based Scale Invariant Image Feature Detector With Error Resilience,
IP(23), No. 5, May 2014, pp. 2380-2391.
IEEE DOI 1405
Approximation methods BibRef

Huang, W., Wu, L.D.[Ling-Da], Song, H.C.[Han-Chen], Wei, Y.M.[Ying-Mei],
RBRIEF: a robust descriptor based on random binary comparisons,
IET-CV(7), No. 1, 2013, pp. 29-35.
DOI Link 1307
Compare to SURF, BRIEF, ORB. Robust descriptor. BibRef

Krajník, T.[Tomáš], Šváb, J.[Jan], Pedre, S.[Sol], Cížek, P.[Petr], Preucil, L.[Libor],
FPGA-based module for SURF extraction,
MVA(25), No. 3, April 2014, pp. 787-800.
Springer DOI 1404
BibRef

Sun, Y.B.[Yan-Biao], Zhao, L.[Liang], Huang, S.D.[Shou-Dong], Yan, L.[Lei], Dissanayake, G.[Gamini],
L2-SIFT: SIFT feature extraction and matching for large images in large-scale aerial photogrammetry,
PandRS(91), No. 1, 2014, pp. 1-16.
Elsevier DOI 1404
Aerial photogrammetry BibRef

Sun, Y.B.[Yan-Biao], Zhao, L.[Liang], Huang, S.D.[Shou-Dong], Yan, L.[Lei], Dissanayake, G.[Gamini],
Line matching based on planar homography for stereo aerial images,
PandRS(104), No. 1, 2015, pp. 1-17.
Elsevier DOI 1505
Line matching BibRef

Tian, X.L.[Xiao-Lin], Jiao, L.C.[Li-Cheng], Liu, X.L.[Xian-Long], Zhang, X.H.[Xiao-Hua],
Feature integration of EODH and Color-SIFT: Application to image retrieval based on codebook,
SP:IC(29), No. 4, 2014, pp. 530-545.
Elsevier DOI 1404
Image retrieval BibRef

Yang, Z.X.[Zhou-Xin], Kurita, T.[Takio],
Improvements of Local Descriptor in HOG/SIFT by BOF Approach,
IEICE(E97-D), No. 5, May 2014, pp. 1293-1303.
WWW Link. 1405
BibRef
Earlier:
Improvements to the Descriptor of SIFT by BOF Approaches,
ACPR13(95-99)
IEEE DOI 1408
computer vision BibRef

Bai, S.[Shuang], Hou, J.J.[Jian-Jun], Ohnishi, N.[Noboru],
Combining LBP and SIFT in Sparse Coding for Categorizing Scene Images,
IEICE(E97-D), No. 9, September 2014, pp. 2563-2566.
WWW Link. 1410
BibRef

Dellinger, F., Delon, J., Gousseau, Y., Michel, J., Tupin, F.,
SAR-SIFT: A SIFT-Like Algorithm for SAR Images,
GeoRS(53), No. 1, January 2015, pp. 453-466.
IEEE DOI 1410
image registration BibRef

Baber, J.[Junaid], Dailey, M.N.[Matthew N.], Satoh, S.[Shin'ichi], Afzulpurkar, N.[Nitin], Bakhtyar, M.[Maheen],
BIG-OH: BInarization of Gradient Orientation Histograms,
IVC(32), No. 11, 2014, pp. 940-953.
Elsevier DOI 1410
Gradient orientation histograms Quantized SIFT. BibRef

Liu, R.Z.[Run Zong], Tang, Y.Y.[Yuan Yan], Fang, B.[Bin],
Topological Coding and Its Application in the Refinement of SIFT,
Cyber(44), No. 11, November 2014, pp. 2155-2166.
IEEE DOI 1411
affine transforms BibRef

Otero, I.R.[Ives Rey], Delbracio, M.[Mauricio],
Anatomy of the SIFT Method,
IPOL(4), 2014, pp. 370-396.
DOI Link 1412

See also Distinctive Image Features from Scale-Invariant Keypoints. BibRef

Dan, G., Khan, M.A., Fodor, V.,
Characterization of SURF and BRISK Interest Point Distribution for Distributed Feature Extraction in Visual Sensor Networks,
MultMed(17), No. 5, May 2015, pp. 591-602.
IEEE DOI 1505
Cameras BibRef

Oyallon, E.[Edouard], Rabin, J.[Julien],
An Analysis of the SURF Method,
IPOL(5), 2015, pp. 176-218.
DOI Link 1508
Code, SURF. General section:
See also Scale Invariant Features, SIFT, SURF, ASIFT. BibRef

Khan, N.[Nabeel], McCane, B.[Brendan], Mills, S.[Steven],
Better than SIFT?,
MVA(26), No. 6, August 2015, pp. 819-836.
WWW Link. 1508
BibRef

Liu, Y.[Yu], Wang, Z.F.[Zeng-Fu],
Dense SIFT for ghost-free multi-exposure fusion,
JVCIR(31), No. 1, 2015, pp. 208-224.
Elsevier DOI 1508
Multi-exposure fusion BibRef

Stanciu, S.G.[Stefan G.], Tranca, D.E.[Denis E.], Coltuc, D.[Dinu],
Contrast enhancement influences the detection of gradient based local invariant features and the matching of their descriptors,
JVCIR(32), No. 1, 2015, pp. 246-256.
Elsevier DOI 1511
Contrast enhancement BibRef

Huang, M., Mu, Z., Zeng, H.,
Efficient image classification via sparse coding spatial pyramid matching representation of SIFT-WCS-LTP feature,
IET-IPR(10), No. 1, 2016, pp. 61-67.
DOI Link 1601
feature extraction BibRef

Awad, D.[Dounia], Courboulay, V.[Vincent], Revel, A.[Arnaud],
Toward a perceptual object recognition system,
ELCVIA(14), No. 3, 2015, pp. xx-yy.
DOI Link 1601
Thesis summary. BibRef

Awad, D.[Dounia], Courboulay, V.[Vincent], Revel, A.[Arnaud],
A New Hybrid Texture-Perceptual Descriptor: Application CBIR,
ICPR14(1150-1155)
IEEE DOI 1412
BibRef
Earlier:
Saliency Filtering of SIFT Detectors: Application to CBIR,
ACIVS12(290-300).
Springer DOI 1209
Detectors BibRef

Hu, S., Wang, Q., Wang, J., Qin, Z., Ren, K.,
Securing SIFT: Privacy-Preserving Outsourcing Computation of Feature Extractions Over Encrypted Image Data,
IP(25), No. 7, July 2016, pp. 3411-3425.
IEEE DOI 1606
Cloud computing. Computation technique. BibRef

Yang, S.Q.A.[Shu-Qi-Ang], Li, B.[Biao], Zeng, K.[Kun],
SBRISK: speed-up binary robust invariant scalable keypoints,
RealTimeIP(12), No. 3, October 2016, pp. 583-591.
WWW Link. 1610
BibRef

Yum, J., Lee, C.H., Kim, J.S., Lee, H.J.,
A Novel Hardware Architecture With Reduced Internal Memory for Real-Time Extraction of SIFT in an HD Video,
CirSysVideo(26), No. 10, October 2016, pp. 1943-1954.
IEEE DOI 1610
Buffer storage BibRef

Kaplan, A.[Avi], Avraham, T.[Tamar], Lindenbaum, M.[Michael],
Interpreting the Ratio Criterion for Matching SIFT Descriptors,
ECCV16(V: 697-712).
Springer DOI 1611
BibRef

Koutaki, G.[Gou], Uchimura, K.[Keiichi],
XY-Separable Scale-Space Filtering by Polynomial Representations and Its Applications,
IEICE(E100-D), No. 4, April 2017, pp. 645-654.
WWW Link. 1704
BibRef
Earlier:
Scale-Space Processing Using Polynomial Representations,
CVPR14(2744-2751)
IEEE DOI 1409
PCA; SIFT; Scale space; Spectral Decomposition BibRef

Kavitha, H., Sudhamani, M.V.,
Experimental analysis of SIFT and SURF features for multi-object image retrieval,
IJCVR(7), No. 3, 2017, pp. 344-356.
DOI Link 1704
BibRef

Yang, F.[Feng], Ma, Z.[Zheng], Xie, M.[Mei],
Codebook Learning for Image Recognition Based on Parallel Key SIFT Analysis,
IEICE(E100-D), No. 4, April 2017, pp. 927-930.
WWW Link. 1704
BibRef

Zhang, W., Wu, X., Zhu, W.P., Yu, L.,
Unsupervized Image Clustering With SIFT-Based Soft-Matching Affinity Propagation,
SPLetters(24), No. 4, April 2017, pp. 461-464.
IEEE DOI 1704
feature extraction BibRef

Hassner, T.[Tal], Filosof, S.[Shay], Mayzels, V.[Viki], Zelnik-Manor, L.[Lihi],
SIFTing Through Scales,
PAMI(39), No. 7, July 2017, pp. 1431-1443.
IEEE DOI 1706
BibRef
Earlier: A1, A3, A4, Only:
On SIFTs and their scales,
CVPR12(1522-1528).
IEEE DOI 1208
Detectors, Estimation, Feature extraction, Laplace equations, Optical imaging, Optimization, Robustness, Vision and scene understanding, and transforms, data structures, representations BibRef

de Lima, R.[Roberto], Martinez-Carranza, J.[Jose], Morales-Reyes, A.[Alicia], Cumplido, R.[Rene],
Improving the construction of ORB through FPGA-based acceleration,
MVA(28), No. 5-6, August 2017, pp. 525-537.
Springer DOI 1708

See also ORB: An efficient alternative to SIFT or SURF. BibRef

Lin, B.W.[Bao-Wei], Wang, F.S.[Fa-Sheng], Sun, Y.[Yi], Qu, W.[Wen], Chen, Z.[Zheng], Zhang, S.[Shuo],
Boundary points based scale invariant 3D point feature,
JVCIR(48), No. 1, 2017, pp. 136-148.
Elsevier DOI 1708
3D, point, clouds BibRef

Lin, B.W.[Bao-Wei], Zhao, F.[Fangda], Tamaki, T.[Toru], Wang, F.S.[Fa-Sheng], Xiao, L.[Le],
SIPF: Scale invariant point feature for 3D point clouds,
ICIP15(2611-2615)
IEEE DOI 1512
SIPF; feature; point cloud; scale invariant BibRef

Sekeroglu, K.[Kazim], Soysal, Ö.M.[Ömer Muhammet],
Comparison of SIFT, Bi-SIFT, and Tri-SIFT and their frequency spectrum analysis,
MVA(28), No. 8, November 2017, pp. 875-902.
WWW Link. 1710
BibRef

Lee, C., Rhee, C.E., Lee, H.J.,
Complexity Reduction by Modified Scale-Space Construction in SIFT Generation Optimized for a Mobile GPU,
CirSysVideo(27), No. 10, October 2017, pp. 2246-2259.
IEEE DOI 1710
Feature extraction, Graphics processing units, Image resolution, Mobile communication, Real-time systems, BibRef

Liu, L.F.[Li-Feng], Ma, Y.[Yan], Zhang, X.F.[Xiang-Fen], Zhang, Y.P.[Yu-Ping], Li, S.[Shunbao],
High discriminative SIFT feature and feature pair selection to improve the bag of visual words model,
IET-IPR(11), No. 11, November 2017, pp. 994-1001.
DOI Link 1711
BibRef

Yum, J., Lee, C., Park, J., Kim, J., Lee, H.,
A Hardware Architecture for the Affine-Invariant Extension of SIFT,
CirSysVideo(28), No. 11, November 2018, pp. 3251-3261.
IEEE DOI 1811
Transforms, Hardware, Real-time systems, Cameras, Memory management, Streaming media, Solids, Hardware accelerator, affine transform hardware BibRef

Desolneux, A., Leclaire, A.,
Stochastic Image Models from SIFT-Like Descriptors,
SIIMS(11), No. 4, 2018, pp. 2305-2338.
DOI Link 1901
BibRef

Liu, Y.J.[Yu-Jie], Yu, D.[Deng], Chen, X.M.[Xiao-Ming], Li, Z.M.[Zong-Min], Fan, J.P.[Jian-Ping],
TOP-SIFT: the selected SIFT descriptor based on dictionary learning,
VC(35), No. 5, May 2019, pp. 667-677.
WWW Link. 1906
BibRef

Cheon, S.H.[Seung Hyeon], Eom, I.K.[Il Kyu], Ha, S.W.[Seok Wun], Moon, Y.H.[Yong Ho],
An enhanced SURF algorithm based on new interest point detection procedure and fast computation technique,
RealTimeIP(16), No. 4, August 2019, pp. 1177-1187.
Springer DOI 1908
BibRef

Wang, R.[Rui], Shi, Y.J.[Yi-Jie], Cao, W.M.[Wen-Ming],
GA-SURF: A new Speeded-Up robust feature extraction algorithm for multispectral images based on geometric algebra,
PRL(127), 2019, pp. 11-17.
Elsevier DOI 1911
Speeded-Up robust features (SURF), Interest points, Geometric algebra (GA), Multispectral image BibRef

Huang, Y.F.[Yin-Fu], Wu, H.Y.[Huan-Yu],
Image retrieval based on ASIFT features in a Hadoop clustered system,
IET-IPR(14), No. 1, January 2020, pp. 138-146.
DOI Link 1912
more efficient computation of ASIFT. BibRef

Doménech-Asensi, G.[Ginés], Zapata-Pérez, J.[Juan], Ruiz-Merino, R.[Ramón], López-Alcantud, J.A.[José Alejandro], Díaz-Madrid, J.Á.[José Ángel], Brea, V.M.[Víctor Manuel], López, P.[Paula],
All-hardware SIFT implementation for real-time VGA images feature extraction,
RealTimeIP(17), No. 2, April 2020, pp. 371-382.
WWW Link. 2004
BibRef

Divya, S.V., Paul, S.[Sourabh], Pati, U.C.[Umesh Chandra],
Structure tensor-based SIFT algorithm for SAR image registration,
IET-IPR(14), No. 5, 17 April 2020, pp. 929-938.
DOI Link 2004
BibRef

Li, D.[Dan], Xu, Q.[Qiannan], Yu, W.[Wennian], Wang, B.[Bing],
SRP-AKAZE: an improved accelerated KAZE algorithm based on sparse random projection,
IET-CV(14), No. 4, June 2020, pp. 131-137.
DOI Link 2005
BibRef

Du, S.L.[Song-Lin], Li, Y.[Yuan], Ikenaga, T.[Takeshi],
Temporally Forward Nonlinear Scale Space for High Frame Rate and Ultra-Low Delay A-KAZE Matching System,
IEICE(E103-D), No. 6, June 2020, pp. 1226-1235.
WWW Link. 2006
BibRef
Earlier: A2, A1, A3:
Temporally Forward Nonlinear Scale Space with Octave Prediction for High Frame Rate and Ultra-Low Delay A-KAZE Matching System,
MVA19(1-4)
DOI Link 1911
Gray codes, motion estimation, forward nonlinear scale space, octave prediction, ultra-low delay, A-KAZE matching system, Robustness
See also KAZE Features. BibRef

Karimi, H.S.[Hiwa Sufi], Mohammadi, K.[Karim],
Rotational invariant biologically inspired object recognition,
IET-IPR(14), No. 15, 15 December 2020, pp. 3762-3773.
DOI Link 2103
Biologically inspired hierarchical model and X (HMAX). Propose a Rotationally invarient version. BibRef

Zhang, M.[Meng], Jin, H.Y.[Hai-Yan], Xiao, Z.L.[Zhao-Lin], Guillemot, C.[Christine],
A Light Field FDL-HCGH Feature in Scale-Disparity Space,
IP(31), 2022, pp. 6164-6174.
IEEE DOI 2210
BibRef
Earlier: A3, A1, A2, A4:
A Light Field FDL-HSIFT Feature in Scale-Disparity Space,
ICIP21(1549-1553)
IEEE DOI 2201
Feature extraction, Light fields, Histograms, Feature detection, Detectors, Computational complexity, Light field, feature description. Statistical analysis, Imaging, Distortion, Fourier disparity layer BibRef

Bellavia, F.[Fabio],
SIFT Matching by Context Exposed,
PAMI(45), No. 2, February 2023, pp. 2445-2457.
IEEE DOI 2301
Detectors, Artificial neural networks, Benchmark testing, Transforms, Training, Pipelines, Merging, Delaunay triangulation, SIFT BibRef

Courbot, J.B.[Jean-Baptiste], Moukadem, A.[Ali], Colicchio, B.[Bruno], Dieterlen, A.[Alain],
Sparse Off-the-Grid Computation of the Zeros of STFT,
SPLetters(30), 2023, pp. 788-792.
IEEE DOI 2307
White noise, Shape, Signal processing algorithms, TV, Time-frequency analysis, Numerical models, Topology, zeros of the STFT BibRef

Barath, D.[Daniel],
On Making SIFT Features Affine Covariant,
IJCV(131), No. 9, September 2023, pp. 2316-2332.
Springer DOI 2308
BibRef
Earlier:
Recovering Affine Features from Orientation- and Scale-Invariant Ones,
ACCV18(I:266-281).
Springer DOI 1906
BibRef

Liu, X.[Xiang], Zhao, X.[Xueli], Xia, Z.H.[Zhi-Hua], Feng, Q.[Qian], Yu, P.[Peipeng], Weng, J.[Jian],
Secure Outsourced SIFT: Accurate and Efficient Privacy-Preserving Image SIFT Feature Extraction,
IP(32), 2023, pp. 4635-4648.
IEEE DOI 2309
BibRef

Xue, Y.Y.[Yong-Yuan], Gao, T.H.[Tian-Han],
Feature Point Extraction and Matching Method Based on Akaze in Illumination Invariant Color Space,
ICIVC20(160-165)
IEEE DOI 2009

See also KAZE Features. Feature extraction, Lighting, Simultaneous localization and mapping, Histograms, Dark channel prior theory BibRef

Rodríguez, M., Facciolo, G., von Gioi, R.G., Musé, P., Morel, J., Delon, J.,
SIFT-AID: Boosting Sift With an Affine Invariant Descriptor Based on Convolutional Neural Networks,
ICIP19(4225-4229)
IEEE DOI 1910
image comparison, affine invariance, IMAS, SIFT, RootSIFT, convolutional neural networks. BibRef