7.1.8.1 Local Features, Computation, Analysis

Li, Y.H.[Yu-Hua], Maguire, L.[Liam],
Selecting Critical Patterns Based on Local Geometrical and Statistical Information,
PAMI(33), No. 6, June 2011, pp. 1189-1201.
IEEE DOI 1105
Find critical patterns that capture information for all classifiers. Edges, borders of separate classes. BibRef

Raytchev, B.[Bisser], Kikutsugi, Y.[Yuta], Tamaki, T.[Toru], Kaneda, K.[Kazufumi],
Embedding class information into local invariant features by low-dimensional retinotopic mapping,
MVA(24), No. 2, February 2013, pp. 407-418.
WWW Link. 1302
projecting the original feature descriptors into low-dimensional feature space BibRef

Li, H., Wei, Y., Li, L., Chen, C.L.P.[C.L. Philip],
Hierarchical Feature Extraction With Local Neural Response for Image Recognition,
Cyber(43), No. 2, April 2013, pp. 412-424.
IEEE DOI 1303
alternating between local coding and maximum pooling. BibRef

Zhou, Y., Panetta, K.A., Agaian, S.S., Chen, C.L.P.,
(n, k, p)-Gray Code for Image Systems,
Cyber(43), No. 2, April 2013, pp. 515-529.
IEEE DOI 1303
BibRef

Bruna, J.[Joan], Mallat, S.[Stephane],
Invariant Scattering Convolution Networks,
PAMI(35), No. 8, 2013, pp. 1872-1886.
IEEE DOI 1307
BibRef
Earlier:
Classification with scattering operators,
CVPR11(1561-1566).
IEEE DOI 1106
convolution networks; deformations; invariants; wavelets. Local descriptor including multiscale and multi-direction co-occurrence information computed with wavelet decompositions. Translation invariant image representation stable to deformations. BibRef

Martins, P., Carvalho, P., Gatta, C.,
Context-aware features and robust image representations,
JVCIR(25), No. 2, 2014, pp. 339-348.
Elsevier DOI 1402
Local features. BibRef

Huang, Z.Y.[Ze-Yi], Kang, W.X.[Wen-Xiong], Wu, Q.X.[Qiu-Xia], Chen, X.P.[Xiao-Peng],
A new descriptor resistant to affine transformation and monotonic intensity change,
CVIU(120), No. 1, 2014, pp. 117-125.
Elsevier DOI 1403
Local invariant descriptor. Resistant to Affine Transformation and Monotonic Intensity Change (RATMIC). BibRef

Tuytelaars, T.[Tinne], Mikolajczyk, K.[Krystian],
Local Invariant Feature Detectors: A Survey,
FTCGV(3), Issue 3, 2007, pp. 177-280.
DOI Link 1410
Survey, Features. Published June 2008. BibRef

Xu, Y.C.[Yong-Chao], Monasse, P., Géraud, T.[Thierry], Najman, L.[Laurent],
Tree-Based Morse Regions: A Topological Approach to Local Feature Detection,
IP(23), No. 12, December 2014, pp. 5612-5625.
IEEE DOI 1412
feature extraction BibRef

Xu, Y.C.[Yong-Chao], Géraud, T.[Thierry], Najman, L.[Laurent],
Connected Filtering on Tree-Based Shape-Spaces,
PAMI(38), No. 6, June 2016, pp. 1126-1140.
IEEE DOI 1605
Filtering
See also Hierarchical Segmentation Using Tree-Based Shape Spaces. BibRef

Chen, S.H.[Shu-Han], Shi, W.R.[Wei-Ren], Lv, X.[Xiao],
Feature coding for image classification combining global saliency and local difference,
PRL(51), No. 1, 2015, pp. 44-49.
Elsevier DOI 1412
Image classification BibRef

Altintakan, U.L., Yazici, A.,
Towards Effective Image Classification Using Class-Specific Codebooks and Distinctive Local Features,
MultMed(17), No. 3, March 2015, pp. 323-332.
IEEE DOI 1502
Clustering methods BibRef

Yan, P.[Pu], Tang, J.[Jun], Zhu, M.[Ming], Liang, D.[Dong],
Local image descriptor based on spectral embedding,
IET-CV(9), No. 2, 2015, pp. 278-289.
DOI Link 1506
graph theory BibRef

Kang, W., Chen, X.,
Fast Representation Based on a Double Orientation Histogram for Local Image Descriptors,
IP(24), No. 10, October 2015, pp. 2915-2927.
IEEE DOI 1507
Detectors BibRef

Gao, Y.Q.[Yong-Qiang], Huang, W.L.[Wei-Lin], Qiao, Y.[Yu],
Local Multi-Grouped Binary Descriptor With Ring-Based Pooling Configuration and Optimization,
IP(24), No. 12, December 2015, pp. 4820-4833.
IEEE DOI 1512
computer vision BibRef

Shaban, A., Rabiee, H.R., Najibi, M., Yousefi, S.,
From Local Similarities to Global Coding: A Framework for Coding Applications,
IP(24), No. 12, December 2015, pp. 5074-5085.
IEEE DOI 1512
Dictionaries BibRef

Lee, M.H.[Man Hee], Cho, M.[Minsu], Park, I.K.[In Kyu],
Feature description using local neighborhoods,
PRL(68, Part 1), No. 1, 2015, pp. 76-82.
Elsevier DOI 1512
Feature description BibRef

Wu, S.[Song], Oerlemans, A.[Ard], Bakker, E.M.[Erwin M.], Lew, M.S.[Michael S.],
A comprehensive evaluation of local detectors and descriptors,
SP:IC(59), No. 1, 2017, pp. 150-167.
Elsevier DOI 1711
Local detector BibRef

Sedaghat, A.[Amin], Mohammadi, N.[Nazila],
Uniform competency-based local feature extraction for remote sensing images,
PandRS(135), No. Supplement C, 2018, pp. 142-157.
Elsevier DOI 1712
Image matching, Feature detector, Scale and space distribution, Robustness, Performance evaluation BibRef

Pham, M.T.[Minh-Tan], Lefèvre, S.[Sébastien], Aptoula, E.[Erchan],
Local Feature-Based Attribute Profiles for Optical Remote Sensing Image Classification,
GeoRS(56), No. 2, February 2018, pp. 1199-1212.
IEEE DOI 1802
Feature extraction, Histograms, Hyperspectral imaging, Standards, Attribute profiles (APs), local feature-based APs (LFAPs), supervised classification BibRef

Song, T.C.[Tie-Cheng], Li, H.L.[Hong-Liang], Meng, F.[Fanman], Wu, Q.B.[Qing-Bo], Luo, B.[Bing], Zeng, B.[Bing], Gabbouj, M.,
Noise-Robust Texture Description Using Local Contrast Patterns via Global Measures,
SPLetters(21), No. 1, January 2014, pp. 93-96.
IEEE DOI 1402
Gaussian noise BibRef

Song, T.C.[Tie-Cheng], Meng, F.[Fanman], Luo, B.[Bing], Huang, C.[Chao],
Robust texture representation by using binary code ensemble,
VCIP13(1-6)
IEEE DOI 1402
binary codes BibRef

Song, T.C.[Tie-Cheng], Xin, L.L.[Liang-Liang], Gao, C.Q.[Chen-Qiang], Zhang, G.[Gang], Zhang, T.Q.[Tian-Qi],
Grayscale-Inversion and Rotation Invariant Texture Description Using Sorted Local Gradient Pattern,
SPLetters(25), No. 5, May 2018, pp. 625-629.
IEEE DOI 1805
feature extraction, gradient methods, image classification, image coding, image texture, sorting, LGP feature extraction, LGP_CR, texture feature BibRef

Song, T.C.[Tie-Cheng], Feng, J.[Jie], Luo, L.[Lin], Gao, C.Q.[Chen-Qiang], Li, H.L.[Hong-Liang],
Robust Texture Description Using Local Grouped Order Pattern and Non-Local Binary Pattern,
CirSysVideo(31), No. 1, January 2021, pp. 189-202.
IEEE DOI 2101
Encoding, Histograms, Feature extraction, Transforms, Computational modeling, Face, Databases, Texture classification, noise BibRef

Han, Y.J.[Yuan-Jing], Song, T.C.[Tie-Cheng], Feng, J.[Jie], Xie, Y.[Yurui],
Grayscale-inversion and rotation invariant image description with sorted LBP features,
SP:IC(99), 2021, pp. 116491.
Elsevier DOI 2111
Image feature, Illumination, Rotation, Invariance, Local binary pattern, Texture classification BibRef

Song, T.C.[Tie-Cheng], Han, Y.J.[Yuan-Jing], Feng, J.[Jie], Wang, Y.L.[Yuan-Lin], Gao, C.Q.[Chen-Qiang],
First- and Second-Order Sorted Local Binary Pattern Features for Grayscale-Inversion and Rotation Invariant Texture Classification,
ICPR21(3706-3713)
IEEE DOI 2105
Histograms, Databases, Gray-scale, Feature extraction, Encoding, Pattern recognition, Sorting, Texture classification, local binary pattern BibRef

Huang, Y.[Yankai], Song, T.C.[Tie-Cheng], Li, S.[Shuang], Han, Y.J.[Yuan-Jing],
Local Grouped Invariant Order Pattern for Grayscale-Inversion and Rotation Invariant Texture Classification,
ICPR21(6632-6639)
IEEE DOI 2105
Histograms, Gray-scale, Image representation, Encoding, Pattern recognition BibRef

Song, T.C.[Tie-Cheng], Luo, L.[Lin], Xin, L.L.[Liang-Liang], Gao, C.Q.[Chen-Qiang],
Multi-Scale Cross-Band Encoding of Sectored Local Binary Pattern for Robust Texture Classification,
ICPR18(1163-1168)
IEEE DOI 1812
Histograms, Image coding, Feature extraction, Databases, Robustness, Encoding, Texture classification, feature extraction, Local Binary Pattern (LBP) BibRef

Song, T.C.[Tie-Cheng], Xin, L.L.[Liang-Liang], Luo, L.[Lin], Gao, C.Q.[Chen-Qiang],
Completed Grayscale-Inversion and Rotation Invariant Local Binary Pattern for Texture Classification,
ICPR18(2642-2647)
IEEE DOI 1812
Lighting, Histograms, Encoding, Gray-scale, Feature extraction, Binary codes, Image coding BibRef

Chakraborti, T., McCane, B., Mills, S., Pal, U.,
LOOP Descriptor: Local Optimal-Oriented Pattern,
SPLetters(25), No. 5, May 2018, pp. 635-639.
IEEE DOI 1805
biology computing, computational complexity, feature extraction, image texture, object recognition, optimisation, GitHub, local optimal oriented pattern (LOOP) BibRef

Huang, Z.D.[Zhou-Di], Wei, Z.Z.[Zhen-Zhong], Zhang, G.J.[Guang-Jun],
RWBD: Learning Robust Weighted Binary Descriptor for Image Matching,
CirSysVideo(28), No. 7, July 2018, pp. 1553-1564.
IEEE DOI 1807
Features for matching. Benchmark testing, Fans, Image matching, Kernel, Object recognition, Real-time systems, Robustness, Binary descriptor, Gaussian kernel, image matching BibRef

Awan, A.B.[Ahmed B.], Rehman, S.[Saad], Bakhshi, A.D.[Asim D.],
Composite filtering strategy for improving distortion invariance in object recognition,
IET-IPR(12), No. 8, August 2018, pp. 1499-1509.
DOI Link 1808
BibRef

Schmid, B.J.[Benjamin J.], Adhami, R.[Reza],
Building Descriptors From Local Feature Neighborhoods for Applications in Semi-Dense 3D Reconstruction,
IP(27), No. 11, November 2018, pp. 5491-5500.
IEEE DOI 1809
Descriptor using location, magnitude, and orientation. feature extraction, image matching, image reconstruction, transforms, local feature neighborhoods, semi-dense 3D reconstruction BibRef

Fu, Z.T.[Zhi-Tao], Qin, Q.Q.[Qian-Qing], Luo, B.[Bin], Sun, H.[Hong], Wu, C.[Chun],
HOMPC: A Local Feature Descriptor Based on the Combination of Magnitude and Phase Congruency Information for Multi-Sensor Remote Sensing Images,
RS(10), No. 8, 2018, pp. xx-yy.
DOI Link 1809
BibRef

Mandeljc, R.[Rok], Maver, J.[Jasna],
AGs: Local descriptors derived from the dependent effects model,
JVCIR(58), 2019, pp. 503-514.
Elsevier DOI 1901
Local image descriptor, Dependent effects model, Image matching, Keypoint descriptor evaluation BibRef

Du, H.S.[Hai-Shun], Li, G.D.[Guo-Dong], Wang, S.[Sheng], Zhang, F.[Fan],
Discriminant locality preserving projections based on L2,p-norm for image feature extraction and recognition,
JVCIR(58), 2019, pp. 166-177.
Elsevier DOI 1901
Discriminant locality preserving projections, Subspace learning, Feature extraction, Image recognition BibRef

Bianconi, F.[Francesco], González, E.[Elena],
Counting local n-ary patterns,
PRL(117), 2019, pp. 24-29.
Elsevier DOI 1901
Mathematical analysis of various local features. Local image descriptors, Patterns, Necklaces, Bracelets BibRef

Elhaouari, K.[Kobzili], Cherif, L.[Larbes],
GMD: geometric model-based local binary descriptor,
SIViP(13), No. 2, March 2019, pp. 289-297.
Springer DOI 1904
Local features on a patch. BibRef

Lin, K.[Kevin], Lu, J.W.[Ji-Wen], Chen, C.S.[Chu-Song], Zhou, J.[Jie], Sun, M.T.[Ming-Ting],
Unsupervised Deep Learning of Compact Binary Descriptors,
PAMI(41), No. 6, June 2019, pp. 1501-1514.
IEEE DOI 1905
BibRef
Earlier: A1, A2, A3, A4, Only:
Learning Compact Binary Descriptors with Unsupervised Deep Neural Networks,
CVPR16(1183-1192)
IEEE DOI 1612
Binary codes, Neural networks, Machine learning, Optimization, Task analysis, Visualization, Quantization (signal), convolutional neural networks. Learn a local descriptor for top level of layered network. BibRef

Wang, Z.[Ziwei], Lu, J.W.[Ji-Wen], Wu, Z.[Ziyi], Zhou, J.[Jie],
Learning Efficient Binarized Object Detectors With Information Compression,
PAMI(44), No. 6, June 2022, pp. 3082-3095.
IEEE DOI 2205
Detectors, Object detection, Redundancy, Complexity theory, Feature extraction, Quantization (signal), Mutual information, sparse priors BibRef

Duan, Y.Q.[Yue-Qi], Lu, J.W.[Ji-Wen], Wang, Z.W.[Zi-Wei], Feng, J.J.[Jian-Jiang], Zhou, J.[Jie],
Learning Deep Binary Descriptor with Multi-Quantization,
PAMI(41), No. 8, August 2019, pp. 1924-1938.
IEEE DOI 1907
BibRef
Earlier: CVPR17(4857-4866)
IEEE DOI 1711
Binary codes, Quantization (signal), Learning systems, Machine learning, Encoding, Resource management, K-Autoencoders. Image reconstruction, Training. BibRef

Kabbai, L.[Leila], Abdellaoui, M.[Mehrez], Douik, A.[Ali],
Image classification by combining local and global features,
VC(35), No. 5, May 2019, pp. 679-693.
Springer DOI 1906
Image feature extraction. Modified version of local ternary pattern. BibRef

Guo, W.L.[Wu-Long], Hu, W.D.[Wei-Duo], Liu, C.[Chang], Lu, T.T.[Ting-Ting],
3D object recognition from cluttered and occluded scenes with a compact local feature,
MVA(30), No. 4, June 2019, pp. 763-783.
Springer DOI 1906
BibRef

Moren, K.[Konrad], Göhringer, D.[Diana],
A framework for accelerating local feature extraction with OpenCL on multi-core CPUs and co-processors,
RealTimeIP(16), No. 4, August 2019, pp. 901-918.
WWW Link. 1908
BibRef

Leyva, R.[Roberto], Sanchez, V.[Victor], Li, C.T.[Chang-Tsun],
Compact and Low-Complexity Binary Feature Descriptor and Fisher Vectors for Video Analytics,
IP(28), No. 12, December 2019, pp. 6169-6184.
IEEE DOI 1909
Feature extraction, Trajectory, Task analysis, Optical imaging, Encoding, Image coding, Computational complexity, Binary features, CNN BibRef

Sadeghi, B.[Bahman], Jamshidi, K.[Kamal], Vafaei, A.[Abbas], Monadjemi, S.A.[S. Amirhassan],
A local image descriptor based on radial and angular gradient intensity histogram for blurred image matching,
VC(35), No. 10, October 2018, pp. 1373-1391.
Springer DOI 1909
BibRef

Zhang, D.B.[Dong-Bo], Yi, L.[Lianglin], Tang, H.Z.[Hong-Zhong], Zhang, Y.[Ying], Xu, H.X.[Hai-Xia],
Multi-scale microstructure binary pattern extraction and learning for image representation,
IET-IPR(13), No. 13, November 2019, pp. 2507-2515.
DOI Link 1911
BibRef

An, F.P.[Feng-Ping], Liu, Z.W.[Zhi-Wen],
Image Processing Algorithm Based on Bi-dimensional Local Mean Decomposition,
JMIV(61), No. 9, November 2019, pp. 1243-1257.
Springer DOI 1911
Image decomposition. BibRef

Xompero, A.[Alessio], Lanz, O.[Oswald], Cavallaro, A.[Andrea],
A Spatio-Temporal Multi-Scale Binary Descriptor,
IP(29), 2020, pp. 4362-4375.
IEEE DOI 2002
BibRef
Earlier:
MORB: A Multi-Scale Binary Descriptor,
ICIP18(2167-2171)
IEEE DOI 1809
Binary descriptor, spatio-temporal feature, multi-scale. Feature extraction, Detectors, Latches, Hamming distance, Robustness, Transforms, Life estimation, Local features, Feature matching, MORB BibRef

Hammouda, G.[Ghassen], Sellami, D.[Dorra], Hammouda, A.[Atef],
Pattern recognition based on compound complex shape-invariant Radon transform,
VC(36), No. 2, February 2020, pp. 279-290.
WWW Link. 2002
BibRef

Ye, J.M.[Jian-Ming], Zhang, S.L.[Shi-Liang], Huang, T.J.[Tie-Jun], Rui, Y.[Yong],
CDbin: Compact Discriminative Binary Descriptor Learned With Efficient Neural Network,
CirSysVideo(30), No. 3, March 2020, pp. 862-874.
IEEE DOI 2003
Learn descriptors (local features) for matching. Feature extraction, Binary codes, Training, Quantization (signal), Neural networks, Task analysis, Correlation, Image patch matching, convolutional neural networks BibRef

Suárez, I.[Iago], Sfeir, G.[Ghesn], Buenaposada, J.M.[José M.], Baumela, L.[Luis],
BEBLID: Boosted efficient binary local image descriptor,
PRL(133), 2020, pp. 366-372.
Elsevier DOI 2005
BibRef
Earlier:
BELID: Boosted Efficient Local Image Descriptor,
IbPRIA19(I:449-460).
Springer DOI 1910
Local image descriptors, Binary descriptors, Real-time, Efficient matching, Boosting BibRef

Wu, G.S.[Geng-Shen], Lin, Z.J.[Zi-Jia], Ding, G.G.[Gui-Guang], Ni, Q.A.[Qi-Ang], Han, J.G.[Jun-Gong],
On Aggregation of Unsupervised Deep Binary Descriptor With Weak Bits,
IP(29), 2020, pp. 9266-9278.
IEEE DOI 2010
Unsupervised Deep Binary Descriptor (UDBD). Hamming distance, Binary codes, Task analysis, Visualization, Manifolds, Robustness, Databases, Image hashing, feature matching, deep learning BibRef

Migliorati, A.[Andrea], Fiandrotti, A.[Attilio], Francini, G.[Gianluca], Leonardi, R.[Riccardo],
Learnable Descriptors for Visual Search,
IP(30), 2021, pp. 80-91.
IEEE DOI 2011
Image coding, Standards, Transform coding, Image matching, Pipelines, Bit rate, Pair-wise image matching, patch matching, fully convolutional neural networks BibRef

Xiao, X., Chen, Y., Gong, Y.J., Zhou, Y.,
Low-Rank Preserving t-Linear Projection for Robust Image Feature Extraction,
IP(30), 2021, pp. 108-120.
IEEE DOI 2011
Feature extraction, Tensors, Data models, Correlation, Data structures, Training, Principal component analysis, tensor-product (t-product) BibRef

Li, Z.[Zhen], Zhao, B.J.[Bao-Jun], Wang, W.Z.[Wen-Zheng],
An Efficient Spectral Feature Extraction Framework for Hyperspectral Images,
RS(12), No. 23, 2020, pp. xx-yy.
DOI Link 2012
BibRef

Ghahremani, M., Liu, Y., Tiddeman, B.,
FFD: Fast Feature Detector,
IP(30), 2021, pp. 1153-1168.
IEEE DOI 2012
Feature extraction, Detectors, Reliability, Dogs, Kernel, Image edge detection, Feature detection, Feature detection, robustness BibRef

Bhattacharjee, D.[Debotosh], Roy, H.[Hiranmoy],
Pattern of Local Gravitational Force (PLGF): A Novel Local Image Descriptor,
PAMI(43), No. 2, February 2021, pp. 595-607.
IEEE DOI 2101
Gravity, Face recognition, Histograms, Feature extraction, Image edge detection, Lighting, Image retrieval, image descriptor BibRef

Sun, T.F.[Tong-Feng], Shao, C.L.[Chang-Long], Liao, H.M.[Hong-Mei], Ding, S.F.[Shi-Fei], Xu, X.Z.[Xin-Zheng],
Research on adaptive local feature enhancement in convolutional neural networks,
IET-IPR(14), No. 16, 19 December 2020, pp. 4306-4315.
DOI Link 2103
BibRef

Kim, T.W.[Tae-Woo],
Feature Detection Based on Significancy of Local Features for Image Matching,
IEICE(E104-D), No. 9, September 2021, pp. 1510-1513.
WWW Link. 2109
BibRef

Feng, Q.P.[Qin-Ping], Tao, S.P.[Shu-Ping], Liu, C.Y.[Chun-Yy], Qu, H.S.[Hong-Song], Xu, W.[Wei],
IFRAD: A Fast Feature Descriptor for Remote Sensing Images,
RS(13), No. 18, 2021, pp. xx-yy.
DOI Link 2109
BibRef

Evenden, E.[Emily], Jr, R.G.P.[Robert Gilmore Pontius],
Encoding a Categorical Independent Variable for Input to TerrSet's Multi-Layer Perceptron,
IJGI(10), No. 10, 2021, pp. xx-yy.
DOI Link 2110
how to code categorical variables for use in learning. BibRef

Chen, L.[Lulu], Zhao, Y.Q.[Yong-Qiang], Chan, J.C.W.[Jonathan Cheung-Wai], Kong, S.G.[Seong G.],
Histograms of oriented mosaic gradients for snapshot spectral image description,
PandRS(183), 2022, pp. 79-93.
Elsevier DOI 2201
Snapshot spectral imaging, Mosaic spatial-spectral gradient operators, Object tracking BibRef

Liu, K.[Kang], Huang, J.[Ju], Li, X.L.[Xue-Long],
Eagle-Eye-Inspired Attention for Object Detection in Remote Sensing,
RS(14), No. 7, 2022, pp. xx-yy.
DOI Link 2205
Foveal analysis. BibRef

Wang, Y.[Yun], Li, Z.[Zhenbo], Li, F.[Fei], Mi, Y.[Yang], Yue, J.[Jun],
Fuzzy Discriminative Block Representation Learning for Image Feature Extraction,
IP(31), 2022, pp. 4994-5008.
IEEE DOI 2208
Sparse matrices, Feature extraction, Task analysis, Representation learning, Optimization, Data models, Data mining, discriminative information preservation BibRef

Luo, H.H.[Hai-Han], Liu, K.[Kai], Jiang, S.[San], Li, Q.Q.[Qing-Quan], Wang, L.Z.[Li-Zhe], Jiang, W.S.[Wan-Shou],
CAISOV: Collinear Affine Invariance and Scale-Orientation Voting for Reliable Feature Matching,
RS(14), No. 13, 2022, pp. xx-yy.
DOI Link 2208
BibRef

Ben Baruch, E.[Elad], Keller, Y.[Yosi],
Joint Detection and Matching of Feature Points in Multimodal Images,
PAMI(44), No. 10, October 2022, pp. 6585-6593.
IEEE DOI 2209
Feature extraction, Detectors, Computer architecture, Measurement, Image sensors, Image edge detection, Training, Deep learning, feature points detection BibRef

Su, J.[Jie], Lu, S.H.[Shu-Han], Li, L.[Lin],
A dual quantum image feature extraction method: PSQIFE,
IET-IPR(16), No. 13, 2022, pp. 3529-3543.
DOI Link 2210
BibRef

Xing, C.D.[Chang-Da], Duan, C.W.[Chao-Wei], Wang, Z.S.[Zhi-Sheng], Wang, M.L.[Mei-Ling],
Binary feature learning with local spectral context-aware attention for classification of hyperspectral images,
PR(134), 2023, pp. 109123.
Elsevier DOI 2212
Classification of hyperspectral images, Local spectrum modules, Spectral context-awareness, Binary feature learning BibRef

Ibrahim, M.R.[Mohamed R.], Lyons, T.[Terry],
ImageSig: A signature transform for ultra-lightweight image recognition,
EVW22(3648-3658)
IEEE DOI 2210
Image edge detection, Memory management, Transforms, Detectors, Streaming media, Feature extraction, Hardware BibRef

Cohen, M.J.[Matan Jacob], Avidan, S.[Shai],
Transformaly: Two (Feature Spaces) Are Better Than One,
L3D-IVU22(4059-4068)
IEEE DOI 2210
Training, Visualization, Pipelines, Computer architecture, Feature extraction BibRef

Xie, Y.Y.[Yu-Yang], Wen, J.H.[Jian-Hong], Lau, K.W.[Kin Wai], Rehman, Y.A.U.[Yasar Abbas Ur], Shen, J.J.[Jia-Jun],
What Should Be Equivariant In Self-Supervised Learning,
L3D-IVU22(4110-4119)
IEEE DOI 2210
Conferences, Self-supervised learning, Cells (biology), Feature extraction, Distortion, Birds BibRef

Revaud, J.[Jérome], Leroy, V.[Vincent], Weinzaepfel, P.[Philippe], Chidlovskii, B.[Boris],
PUMP: Pyramidal and Uniqueness Matching Priors for Unsupervised Learning of Local Descriptors,
CVPR22(3916-3926)
IEEE DOI 2210
Location awareness, Training, Visualization, Image matching, Pipelines, Training data, Pattern recognition, Self- semi- meta- unsupervised learning BibRef

Metwaly, K.[Kareem], Kim, A.[Aerin], Branson, E.[Elliot], Monga, V.[Vishal],
GlideNet: Global, Local and Intrinsic based Dense Embedding NETwork for Multi-category Attributes Prediction,
CVPR22(4825-4836)
IEEE DOI 2210
Training, Shape, Convolution, Taxonomy, Computer architecture, Predictive models, Recognition: detection, categorization, Self- semi- meta- unsupervised learning BibRef

Li, K.H.[Kun-Hong], Wang, L.G.[Long-Guang], Liu, L.[Li], Ran, Q.[Qing], Xu, K.[Kai], Guo, Y.L.[Yu-Lan],
Decoupling Makes Weakly Supervised Local Feature Better,
CVPR22(15817-15827)
IEEE DOI 2210
Training, Representation learning, Pipelines, Supervised learning, Cameras, Search problems, 3D from multi-view and sensors, Self- semi- meta- unsupervised learning BibRef

Zhi, S.F.[Shuai-Feng], Laidlow, T.[Tristan], Leutenegger, S.[Stefan], Davison, A.J.[Andrew J.],
In-Place Scene Labelling and Understanding with Implicit Scene Representation,
ICCV21(15818-15827)
IEEE DOI 2203
Geometry, Visualization, Interpolation, Shape, Semantics, Superresolution, Noise reduction, 3D from multiview and other sensors BibRef

Assran, M.[Mahmoud], Caron, M.[Mathilde], Misra, I.[Ishan], Bojanowski, P.[Piotr], Joulin, A.[Armand], Ballas, N.[Nicolas], Rabbat, M.[Michael],
Semi-Supervised Learning of Visual Features by Non-Parametrically Predicting View Assignments with Support Samples,
ICCV21(8423-8432)
IEEE DOI 2203
Training, Visualization, Computer architecture, Semisupervised learning, Representation learning BibRef

Wang, B.[Bing], Chen, C.[Changhao], Cui, Z.P.[Zhao-Peng], Qin, J.[Jie], Lu, C.X.X.[Chris Xiao-Xuan], Yu, Z.[Zhengdi], Zhao, P.J.[Pei-Jun], Dong, Z.[Zhen], Zhu, F.[Fan], Trigoni, N.[Niki], Markham, A.[Andrew],
P2-Net: Joint Description and Detection of Local Features for Pixel and Point Matching,
ICCV21(15984-15993)
IEEE DOI 2203
Point cloud compression, Location awareness, Visualization, Codes, Image matching, Vision for robotics and autonomous vehicles, Vision applications and systems BibRef

Usilin, S.A.[Sergey A.], Slavin, O.A.[Oleg A.], Arlazarov, V.V.[Vladimir V.],
Memory Consumption and Computation Efficiency Improvements of Viola-Jones Object Detection Method for UAVS,
IMTA20(243-252).
Springer DOI 2103

See also Robust Real-Time Face Detection. BibRef

Wang, Q.N.[Qian-Nan], Zhou, Y.[Ying], Zhu, Z.Y.[Zhao-Yan], Liang, X.F.[Xue-Feng], Gu, Y.[Yu],
Jointly Discriminating and Frequent Visual Representation Mining,
ACCV20(III:356-371).
Springer DOI 2103
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Tolias, G.[Giorgos], Jenicek, T.[Tomas], Chum, O.[Ondrej],
Learning and Aggregating Deep Local Descriptors for Instance-Level Recognition,
ECCV20(I:460-477).
Springer DOI 2011
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Pautrat, R.[Rémi], Larsson, V.[Viktor], Oswald, M.R.[Martin R.], Pollefeys, M.[Marc],
Online Invariance Selection for Local Feature Descriptors,
ECCV20(II:707-724).
Springer DOI 2011
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Sun, Y.F.[Yi-Fan], Cheng, C.M.[Chang-Mao], Zhang, Y.H.[Yu-Han], Zhang, C.[Chi], Zheng, L.[Liang], Wang, Z.D.[Zhong-Dao], Wei, Y.C.[Yi-Chen],
Circle Loss: A Unified Perspective of Pair Similarity Optimization,
CVPR20(6397-6406)
IEEE DOI 2008
Optimization, Convergence, Training, Task analysis, Face recognition, Image retrieval, Measurement BibRef

Jenni, S., Jin, H.L., Favaro, P.,
Steering Self-Supervised Feature Learning Beyond Local Pixel Statistics,
CVPR20(6407-6416)
IEEE DOI 2008
Training, Task analysis, Supervised learning, Image representation, Feature extraction, Image recognition, Shape BibRef

Bai, X., Luo, Z., Zhou, L., Fu, H., Quan, L., Tai, C.,
D3Feat: Joint Learning of Dense Detection and Description of 3D Local Features,
CVPR20(6358-6366)
IEEE DOI 2008
Feature extraction, Detectors, Convolution, Kernel, Training BibRef

Shen, Y.T.[Yan-Tao], Xiong, Y.J.[Yuan-Jun], Xia, W.[Wei], Soatto, S.[Stefano],
Towards Backward-Compatible Representation Learning,
CVPR20(6367-6376)
IEEE DOI 2008
Training, Visualization, Task analysis, Feature extraction, Computational modeling, Measurement, Computer architecture BibRef

Bhowmik, A., Gumhold, S., Rother, C., Brachmann, E.,
Reinforced Feature Points: Optimizing Feature Detection and Description for a High-Level Task,
CVPR20(4947-4956)
IEEE DOI 2008
Feature extraction, Task analysis, Training, Pipelines, Detectors, Probabilistic logic, Neural networks BibRef

Chen, K.X.[Kai-Xuan], Wu, X.J.[Xiao-Jun], Ren, J.Y.[Jie-Yi], Wang, R.[Rui], Kittler, J.V.[Josef V.],
More About Covariance Descriptors for Image Set Coding: Log-Euclidean Framework Based Kernel Matrix Representation,
CEFRL19(2923-2932)
IEEE DOI 2004
covariance analysis, covariance matrices, image classification, image coding, image representation, Log Euclidean framework BibRef

Zhang, L., Rusinkiewicz, S.,
Learning Local Descriptors With a CDF-Based Dynamic Soft Margin,
ICCV19(2969-2978)
IEEE DOI 2004
learning (artificial intelligence), hard margin, nonparametric soft margin, binary local feature descriptors, Probability density function BibRef

Yu, X.[Xin], Tian, Y.R.[Yu-Run], Porikli, F.M.[Fatih M.], Hartley, R.I.[Richard I.], Li, H.D.[Hong-Dong], Heijnen, H.[Huub], Balntas, V.[Vassileios],
Unsupervised Extraction of Local Image Descriptors via Relative Distance Ranking Loss,
CEFRL19(2893-2902)
IEEE DOI 2004
convolutional neural nets, feature extraction, learning (artificial intelligence), transforms, local features BibRef

Spencer, J.[Jaime], Bowden, R.[Richard], Hadfield, S.[Simon],
Scale-Adaptive Neural Dense Features: Learning via Hierarchical Context Aggregation,
CVPR19(6193-6202).
IEEE DOI 2002
Features that include spatial context. BibRef

Jamioy, C.J.[Carlos Jacanamejoy], Meneses-Casas, N.[Nohora], Forero, M.G.[Manuel G.],
Image Feature Detection Based on Phase Congruency by Monogenic Filters with New Noise Estimation,
IbPRIA19(I:577-588).
Springer DOI 1910
BibRef

Doiphode, N.[Nehal], Mitra, R.[Rahul], Ahmed, S.[Shuaib], Jain, A.[Arjun],
An Improved Learning Framework for Covariant Local Feature Detection,
ACCV18(VI:262-276).
Springer DOI 1906
BibRef

Xu, Y.[Yanwu], Gong, M.M.[Ming-Ming], Liu, T.[Tongliang], Batmanghelich, K.[Kayhan], Wang, C.[Chaohui],
Robust Angular Local Descriptor Learning,
ACCV18(V:420-435).
Springer DOI 1906
BibRef

Barath, D.[Daniel],
Recovering Affine Features from Orientation- and Scale-Invariant Ones,
ACCV18(I:266-281).
Springer DOI 1906
BibRef

Koçanaogullari, A.[Aziz], Ataer-Cansizoglu, E.[Esra],
Active Descriptor Learning for Feature Matching,
CEFR-LCV18(IV:619-630).
Springer DOI 1905
BibRef

He, K.[Kun], Lu, Y.[Yan], Sclaroff, S.[Stan],
Local Descriptors Optimized for Average Precision,
CVPR18(596-605)
IEEE DOI 1812
Pipelines, Task analysis, Measurement, Feature extraction, Optimization, Histograms, Neural networks BibRef

van Opdenbosch, D.[Dominik], Steinbach, E.[Eckehard],
Flexible Rate Allocation for Local Binary Feature Compression,
ICIP18(3259-3263)
IEEE DOI 1809
Visualization, Encoding, Feature extraction, Task analysis, Vocabulary, Entropy, Visual features, Bag-of-Words, ATC BibRef

Mohtaram, N., Radgui, A., Caron, G., Mouaddib, E.M.,
AMIFT: Affine-Mirror Invariant Feature Transform,
ICIP18(893-897)
IEEE DOI 1809
Mirrors, Cameras, Geometry, Transmission line matrix methods, Transforms, SIFT, reflection invariant feature BibRef

Martins, V.[Valdomiro], Ribeiro, T.P.[Thiago P.], Martinez, A.C.[Ana Claudia], Abdala, D.[Daniel],
Taking the Most of Existing Image Descriptors: A Hybrid Approach,
WVC17(96-101)
IEEE DOI 1804
new image descriptor based on the aggregation of multiple pre-existing image descriptors. feature extraction, image processing, statistical analysis, visual databases, first order statistical measurements, image retrieval BibRef

Arnfred, J.T., Nguyen, V.D., Winkler, S.,
BAFT: Binary affine feature transform,
ICIP17(2821-2825)
IEEE DOI 1803
Detectors, Eigenvalues and eigenfunctions, Feature extraction, Matrix decomposition, Robustness, Transforms, Velocity measurement BibRef

Zhang, X.[Xu], Yu, F.X.[Felix X.], Kumar, S., Chang, S.F.[Shih-Fu],
Learning Spread-Out Local Feature Descriptors,
ICCV17(4605-4613)
IEEE DOI 1802
feature extraction, image representation, learning (artificial intelligence), Training BibRef

Zhang, X.[Xu], Yu, F.X.[Felix X.], Karaman, S.[Svebor], Chang, S.F.[Shih-Fu],
Learning Discriminative and Transformation Covariant Local Feature Detectors,
CVPR17(4923-4931)
IEEE DOI 1711
Detectors, Feature extraction, Robustness, Shape, Standards, Training BibRef

Liao, W.H.[Wen-Hung], Yu, C.[Carolyn], Wu, Y.C.[Yi-Chieh],
Construction and Optimization of Feature Descriptor Based on Dynamic Local Intensity Order Relations of Pixel Group,
ICIAR19(I:364-375).
Springer DOI 1909
BibRef

Liao, W.H.[Wen-Hung], Wu, C.C.[Chia-Chen], Lin, M.C.[Ming-Ching],
Feature descriptor based on local intensity order relations of pixel group,
ICPR16(1977-1981)
IEEE DOI 1705
Benchmark testing, Degradation, Encoding, Histograms, Image recognition, Indexes, Standards, local descriptors, local intensity order patterns (LIOP), local intensity order relations (LIOR) BibRef

Johansson, J.[Johan], Solli, M.[Martin], Maki, A.[Atsuto],
An Evaluation of Local Feature Detectors and Descriptors for Infrared Images,
LocalFea16(III: 711-723).
Springer DOI 1611
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Zhou, H.[Hao], Sattler, T.[Torsten], Jacobs, D.W.[David W.],
Evaluating Local Features for Day-Night Matching,
LocalFea16(III: 724-736).
Springer DOI 1611
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Kang, Y.[Yimei], Li, X.[Xiang],
A Novel Tiny Object Recognition Algorithm Based on Unit Statistical Curvature Feature,
ECCV16(V: 762-777).
Springer DOI 1611
Based on local feature detector BibRef

Ferdowsi, S., Voloshynovskiy, S.[Slava], Kostadinov, D.[Dimche],
A multi-layer image representation using regularized residual quantization: Application to compression and denoising,
ICIP17(2697-2701)
IEEE DOI 1803
Distortion, Image coding, Noise reduction, Principal component analysis, Quantization (signal), learning to compress BibRef

Kostadinov, D.[Dimche], Voloshynovskiy, S.[Slava], Diephuis, M.[Maurits], Ferdowsi, S., Holotyak, T.[Taras],
Local Active Content Fingerprint: Solutions for general linear feature maps,
ICPR16(949-954)
IEEE DOI 1705
BibRef
And: A1, A2, A3, A5, Only:
Local active content fingerprinting: Optimal solution under linear modulation,
ICIP16(3917-3921)
IEEE DOI 1610
Distortion, Feature extraction, Matrix decomposition, Modulation, Quantization (signal), Robustness, Transforms, AWGN. Local, patch-based descriptors. BibRef

Rashwan, H.A.[Hatem A.], Chambon, S.[Sylvie], Gurdjos, P.[Pierre], Morin, G.[Géraldine], Charvillat, V.[Vincent],
Towards multi-scale feature detection repeatable over intensity and depth images,
ICIP16(36-40)
IEEE DOI 1610
Local features at multiple locations. Detectors BibRef

Ferrarini, B.[Bruno], Ehsan, S.[Shoaib], Ur Rehman, N.[Naveed], Leonardis, A.[Ales], McDonald-Maier, K.D.[Klaus D.],
Automatic Selection of the Optimal Local Feature Detector,
ICIAR16(284-289).
Springer DOI 1608
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Ehsan, S.[Shoaib], Clark, A.F., Ferrarini, B., Ur Rehman, N.[Naveed], McDonald-Maier, K.D.[Klaus D.],
Assessing the performance bounds of local feature detectors: Taking inspiration from electronics design practices,
WSSIP15(166-169)
IEEE DOI 1603
data compression BibRef

Rusinol, M.[Maral], Chazalon, J.[Joseph], Ogier, J.M.[Jean-Marc], Llados, J.[Josep],
A comparative study of local detectors and descriptors for mobile document classification,
ICDAR15(596-600)
IEEE DOI 1511
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Saad, S.[Shimaa], Sagheer, A.[Alaa],
Difference-Based Local Gradient Patterns for Image Representation,
CIAP15(II:472-482).
Springer DOI 1511
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Lee, K.D.[Keun-Dong], Lee, S.J.[Seung-Jae], Oh, W.G.[Weon-Geun],
Accelerating Local Feature Extraction Using Two Stage Feature Selection and Partial Gradient Computation,
IMEV14(366-380).
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Feature extraction for MPEG coding. BibRef

Varytimidis, C.[Christos], Rapantzikos, K.[Konstantinos], Avrithis, Y.[Yannis], Kollias, S.[Stefanos],
Improving Local Features by Dithering-Based Image Sampling,
ACCV14(II: 601-613).
Springer DOI 1504
BibRef

Barroso, T.M.[Tony Marrero], Ghita, O.[Ovidiu], Whelan, P.F.[Paul F.],
Evaluating the performance and correlation of colour invariant local image feature detectors,
ICIP14(5751-5755)
IEEE DOI 1502
Correlation BibRef

Kim, W.J.[Won-Jun], Yoo, B.I.[Byung In], Han, J.J.[Jae-Joon],
HDO: A novel local image descriptor,
ICIP14(5671-5675)
IEEE DOI 1502
Coherence BibRef

Margolin, R.[Ran], Zelnik-Manor, L.[Lihi], Tal, A.[Ayellet],
OTC: A Novel Local Descriptor for Scene Classification,
ECCV14(VII: 377-391).
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Oriented Texture Curves (OTC). BibRef

Phan, D.[Dung], Oh, C.M.[Chi-Min], Kim, S.H.[Soo-Hyung], Na, I.S.[In-Seop], Lee, C.W.[Chil-Woo],
Object Recognition by Combining Binary Local Invariant Features and Color Histogram,
ACPR13(466-470)
IEEE DOI 1408
feature extraction BibRef

Iwamoto, K.[Kota], Mase, R.[Ryota], Nomura, T.[Toshiyuki],
BRIGHT: A scalable and compact binary descriptor for low-latency and high accuracy object identification,
ICIP13(2915-2919)
IEEE DOI 1402
Local descriptor BibRef

Ren, W.Q.[Wei-Qiang], Huang, Y.Z.[Yong-Zhen], Zhao, X.[Xin], Huang, K.Q.[Kai-Qi], Tan, T.N.[Tie-Niu],
Local Hypersphere Coding Based on Edges between Visual Words,
ACCV12(I:190-203).
Springer DOI 1304
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Li, S.M.[Shi-Miao], Xiong, W.[Wei],
Glocal shape context descriptor in cluttered images,
ICPR12(3704-3707).
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fine scale edges in center, coarse on outer region. BibRef

Yang, Y.Q.[Yi-Qing], Li, Z.Y.[Zhou-Yuan], Zhang, L.[Li], Murphy, C.J.[Christopher J.], Hoeve, J.V.[Jim Ver], Jiang, H.R.[Hong-Rui],
Local Label Descriptor for Example Based Semantic Image Labeling,
ECCV12(VII: 361-375).
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Label histograms for each cell in a patch. BibRef

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Jet-Based Local Image Descriptors,
ECCV12(III: 638-650).
Springer DOI 1210
based on differential geometry BibRef

Varytimidis, C.[Christos], Rapantzikos, K.[Konstantinos], Avrithis, Y.S.[Yannis S.],
WaSH: Weighted alpha-Shapes for Local Feature Detection,
ECCV12(II: 788-801).
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Medathati, N.V.K.[N.V. Kartheek], Sivaswamy, J.[Jayanthi],
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ICCVGIP10(398-404).
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For region description BibRef

Fan, B.[Bin], Wu, F.C.[Fu-Chao], Hu, Z.Y.[Zhan-Yi],
Aggregating gradient distributions into intensity orders: A novel local image descriptor,
CVPR11(2377-2384).
IEEE DOI 1106
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Lee, W.T.[Wei-Ting], Chen, H.T.[Hwann-Tzong],
Probing the local-feature space of interest points,
ICIP10(857-860).
IEEE DOI 1009
BibRef

Joly, A.[Alexis],
New local descriptors based on dissociated dipoles,
CIVR07(573-580).
DOI Link 0707
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Nakayama, H.[Hideki], Harada, T.[Tatsuya], Kuniyoshi, Y.[Yasuo],
Scene Classification Using Generalized Local Correlation,
MVA09(195-).
PDF File. 0905
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Janney, P.[Pranam], Geers, G.[Glenn],
IFLT Based Real-Time Framework for Image Matching,
ICPR10(2242-2245).
IEEE DOI 1008
Invariant Features of Local Textures (IFLT) BibRef

Lai, Z.H.[Zhi-Hui], Jin, Z.[Zhong], Yang, J.[Jian], Wong, W.K.,
Sparse Local Discriminant Projections for Feature Extraction,
ICPR10(926-929).
IEEE DOI 1008
BibRef

Carneiro, G.[Gustavo],
A Comparative Study on the Use of an Ensemble of Feature Extractors for the Automatic Design of Local Image Descriptors,
ICPR10(3356-3359).
IEEE DOI 1008
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Tang, F.[Feng], Lim, S.H.[Suk Hwan], Chang, N.L.[Nelson L.],
An improved local feature descriptor via soft binning,
ICIP10(861-864).
IEEE DOI 1009
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Cheng, B.S.[Bang-Sheng],
Local tensor descriptor from micro-deformation analysis,
CVPR08(1-8).
IEEE DOI 0806
local image structure BibRef

Garcia-Tubio, M.P.[Manuel Pascual], Wildenauer, H.[Horst], Szumilas, L.[Lech],
Combining Geometry and Local Appearance for Object Detection,
ICPR10(4024-4027).
IEEE DOI 1008
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Vedaldi, A.[Andrea], Soatto, S.[Stefano],
Local Features, All Grown Up,
CVPR06(II: 1753-1760).
IEEE DOI 0606
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Vedaldi, A.[Andrea], Soatto, S.[Stefano],
Viewpoint Induced Deformation Statistics and the Design of Viewpoint Invariant Features: Singularities and Occlusions,
ECCV06(II: 360-373).
Springer DOI 0608
BibRef
Earlier:
Features for Recognition: Viewpoint Invariance for Non-Planar Scenes,
ICCV05(II: 1474-1481).
IEEE DOI 0510
BibRef

Chapter on 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture continues in
Keypoint Detection .