7 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture

Two-Dimensional feature extraction and computation algorithms are described here. Edge detection, region segmentation and texture are covered in later chapters.

7.1 Computation of General Features

Chapter Contents (Back)
Feature Extraction. Fast Algorithms. Parallel Algorithms. Feature Computation.

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Earlier:
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Roth, G.[Gerhard], Levine, M.D.[Martin D.],
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Earlier: CVPR92(640-643).
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And:
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Liu, K.[Ke], Cheng, Y.Q.[Yong-Qing], Yang, J.Y.[Jing-Yu],
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Cinque, L., Lombardi, L.,
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Elsevier DOI 0701
BibRef
Earlier:
Shape recognition by distributed recursive learning of multiscale trees,
CIAP03(26-30).
IEEE DOI 0310
Multiscale tree representation; Syntactic shape recognition; Fuzzy neural networks; Recursive learning BibRef

Levialdi, S., Cinque, L.,
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PRAI(10), 1996, pp. 573-585. BibRef 9600

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Douglas, S.C.,
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Mao, J.C., Jain, A.K.,
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Xin, K., Lim, K.B., Hong, G.S.,
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Rao, A., Perens, B.,
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Chuang, E.R.[E-Ren], Sher, D.[David],
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Benteftifa, M.H., Kurz, L.,
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Meisels, A., Hason, O., Hess, H.,
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IVC(9), No. 3, June 1991, pp. 151-159.
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Hu, X.P., Ahuja, N.,
Feature Extraction and Matching as Signal Detection,
PRAI(8), 1994, pp. 1343-1379. BibRef 9400
Earlier: SPIE(1964), 1993, pp. 51-65. BibRef

Levine, S.H., Kreifeldt, J.G., Chuang, M.C.,
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Levine, S.H., Kreifeldt, J.G.,
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SMC(24), 1994, pp. 895-900. BibRef 9400

Kovalevsky, V.A.[Vladimir A.],
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MDSG94(21). BibRef 9400

Gevorkian, D.Z., Astola, J.T., Atourian, S.M.,
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See also Computing 2-D Min, Median, and Max Filters. BibRef

Shi, H.C., Ritter, G.X., Wilson, J.N.,
A Fast General Algorithm for Extracting Image Features on SIMD Mesh-Connected Computers,
PR(30), No. 7, July 1997, pp. 1205-1211.
Elsevier DOI 9707
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Mirmehdi, M., Palmer, P.L., Kittler, J.V.,
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Robbins, B., Owens, R.,
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Elsevier DOI 9706
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Perona, P.,
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IP(7), No. 3, March 1998, pp. 457-467.
IEEE DOI 9803
BibRef
Earlier: CVPR97(710-716).
IEEE DOI 9704
Edges, lines, corners. Diffusion techniques. BibRef

Baker, S.[Simon], Nayar, S.K.[Shree K.], Murase, H.[Hiroshi],
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IJCV(27), No. 1, March 1998, pp. 27-50.
DOI Link 9805
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Earlier: DARPA97(1425-1430). BibRef
Earlier: A2, A1, A3: CVPR96(471-477).
IEEE DOI Automatically construct feature detectors for parametric features. Examples on edges and corners -- codes distance to the edge/corner manifold. BibRef

Baker, S.[Simon],
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Ph.D.Thesis, September 1998, Department of Computer Science, Columbia University.
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Brailovsky, V.L.,
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Jiang, T.Z., Ma, S.D.,
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IEEE DOI 9608
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Oriat, L., Lantz, E.,
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Nandy, D., Ben-Arie, J.,
Generalized Feature Extraction Using Expansion Matching,
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Wang, Z., Ben-Arie, J.,
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JMIV(20), No. 3, May 2004, pp. 209-222.
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Generate an average shape based on several shapes. Apply to Fundus images and denoising. BibRef

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Kovesi, P.[Peter],
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Kovesi, P.[Peter],
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Earlier:
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Springer DOI 0209
Features correspond to entropy rich areas of the image.
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Ohm, J.R.[Jens-Rainer],
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Radial projections for non-linear feature extraction,
ICPR02(II: 444-447).
IEEE DOI 0211
Statistic pattern recognition; Feature extraction; Genetic algorithms BibRef

Pennec, X.[Xavier],
Intrinsic Statistics on Riemannian Manifolds: Basic Tools for Geometric Measurements,
JMIV(25), No. 1, July 2006, pp. 127-154.
Springer DOI 0610
Tools to deal with noise in feature computation. BibRef

Riesenhuber, M.[Maximilian], Poggio, T.[Tomaso],
Hierarchical models of object recognition in cortex,
Nature:Neuroscience(2), No. 11, November 1999, 1019-1025.
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Riesenhuber, M.[Maximilian], Poggio, T.[Tomaso],
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Nature:Neuroscience(3), No. 11, 2000, 1199-1204.
HTML Version. BibRef 0001

Riesenhuber, M.[Maximilian], Poggio, T.[Tomaso],
Computational Models of Object Recognition in Cortex: A Review,
MIT AI Memo-1695, August 7, 2000.
WWW Link. 0105
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Serre, T.[Thomas], Wolf, L.B.[Lior B.], Bileschi, S.M., Riesenhuber, M., Poggio, T.[Tomaso],
Robust Object Recognition with Cortex-Like Mechanisms,
PAMI(29), No. 3, March 2007, pp. 411-426.
IEEE DOI 0702
BibRef
Earlier: A1, A2, A5, Only:
Object Recognition with Features Inspired by Visual Cortex,
CVPR05(II: 994-1000).
IEEE DOI 0507
Build representation by alternating between template and a maximum pooling operation. Both shape and texture. Learns from a few examples.
See also On the Role of Object-Specific Features for Real World Object Recognition in Biological Vision.
See also Hierarchical models of object recognition in cortex. BibRef

CVonline: Geometric Feature Extraction Methods,
CV-OnlineJuly 2001.
HTML Version. Survey, Feature Extraction. BibRef 0107

Duan, C., Meng, X., Tu, C., Yang, C.,
How to make local image features more efficient and distinctive,
IET-CV(2), No. 3, September 2008, pp. 178-189.
DOI Link 0905
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Huckemann, S.[Stephan], Hotz, T.[Thomas], Munk, A.[Axel],
Intrinsic MANOVA for Riemannian Manifolds with an Application to Kendall's Space of Planar Shapes,
PAMI(32), No. 4, April 2010, pp. 593-603.
IEEE DOI 1003
multifactorial model for planar shapes. BibRef

Huckemann, S.[Stephan], Hotz, T.[Thomas],
On Means and Their Asymptotics: Circles and Shape Spaces,
JMIV(50), No. 1-2, September 2014, pp. 98-106.
WWW Link. 1408
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Bayro-Corrochano, E.[Eduardo],
Geometric Computing for Wavelet Transforms, Robot Vision, Learning, Control and Action,
Springer-Verlag2010.I ISBN: 978-1-84882-928-2
WWW Link. Survey, Feature Computation. Buy this book: Geometric Computing: for Wavelet Transforms, Robot Vision, Learning, Control and Action Various features, geometric computing, FFT, wavelets, graphics. BibRef 1000

Zhu, S.C.[Song-Chun], Shi, K.[Kent], Si, Z.Z.[Zhang-Zhang],
Learning explicit and implicit visual manifolds by information projection,
PRL(31), No. 8, 1 June 2010, pp. 667-685.
Elsevier DOI 1004
Texture; Texton; Image Manifold; Primal sketch; Visual learning; Information projection
See also Learning Hybrid Image Templates (HIT) by Information Projection.
See also Learning AND-OR Templates for Object Recognition and Detection. BibRef

Shi, K.[Kent], Zhu, S.C.[Song-Chun],
Mapping Natural Image Patches by Explicit and Implicit Manifolds,
CVPR07(1-7).
IEEE DOI 0706
Explicit: edges, bars, corners, junctions. Implicit: textures. BibRef

Silva, A.G.[Alexandre Goncalves], de Alencar Lotufo, R.[Roberto],
Efficient computation of new extinction values from extended component tree,
PRL(31), No. 1, January 2010, pp. 79-90.
Elsevier DOI 1011
Component tree; Dynamics; Extinction values; Max-tree Interpret gray-scale image as surface -- valleys, plateaus, etc. extinction values from image extremes. BibRef

Silva, A.G.[Alexandre Gongalves],
Region-based thresholding using component tree,
ICIP11(1445-1448).
IEEE DOI 1201
BibRef

Wang, K.[Ke], Xiao, P.F.[Peng-Feng], Feng, X.Z.[Xue-Zhi], Wu, G.P.[Gui-Ping],
Image feature detection from phase congruency based on two-dimensional Hilbert transform,
PRL(32), No. 15, 1 November 2011, pp. 2015-2024.
Elsevier DOI 1112
Phase congruency; Hilbert transform; Local energy; Feature detection BibRef

Bostanci, E., Kanwal, N.[Nadia], Clark, A.F.[Adrian F.],
Spatial Statistics of Image Features for Performance Comparison,
IP(23), No. 1, January 2014, pp. 153-162.
IEEE DOI 1402
feature extraction BibRef

Kanwal, N.[Nadia], Bostanci, E., Clark, A.F.[Adrian F.],
Matching corners using the informative arc,
IET-CV(8), No. 3, June 2014, pp. 245-253.
DOI Link 1407
BibRef

Fan, B., Kong, Q., Trzcinski, T., Wang, Z., Pan, C., Fua, P.,
Receptive Fields Selection for Binary Feature Description,
IP(23), No. 6, June 2014, pp. 2583-2595.
IEEE DOI 1406
Accuracy BibRef

Fan, B., Kong, Q., Sui, W., Wang, Z., Wang, X., Xiang, S., Pan, C., Fua, P.,
Do We Need Binary Features for 3D Reconstruction?,
Robust16(1126-1135)
IEEE DOI 1612
BibRef

Han, Y.H.[Ya-Hong], Yang, Y.[Yi], Ma, Z.G., Shen, H., Sebe, N., Zhou, X.,
Image Attribute Adaptation,
MultMed(16), No. 4, June 2014, pp. 1115-1126.
IEEE DOI 1407
Between image features and objects. Feature transfer (akin to transfer learning). BibRef

Meng, X.L.[Xiang-Lin], Wang, Z.Z.[Zheng-Zhi], Wu, L.Z.[Li-Zhen],
Building global image features for scene recognition,
PR(45), No. 1, 2012, pp. 373-380.
Elsevier DOI 1410
Scene recognition BibRef

Shen, I.C., Cheng, W.H.,
Gestalt Rule Feature Points,
MultMed(17), No. 4, April 2015, pp. 526-537.
IEEE DOI 1503
Computational modeling. Features that are repeatable across styles (image, painting, sketch). BibRef

Perina, A.[Alessandro], Jojic, N.[Nebojsa],
Capturing Spatial Interdependence in Image Features: The Counting Grid, an Epitomic Representation for Bags of Features,
PAMI(37), No. 12, December 2015, pp. 2374-2387.
IEEE DOI 1512
BibRef
Earlier:
Capturing Layers in Image Collections with Componential Models: From the Layered Epitome to the Componential Counting Grid,
CVPR13(500-507)
IEEE DOI 1309
image representation. Bag of Words BibRef

Perina, A.[Alessandro], Cristani, M.[Marco], Murino, V.[Vittorio], Jojic, N.[Nebojsa],
Capturing Video Structure with Mixture of Probabilistic Index Maps,
MLMotion08(xx-yy). 0810
BibRef

Jojic, N., Caspi, Y.[Yaron],
Capturing Image Structure with Probabilistic Index Maps,
CVPR04(I: 212-219).
IEEE DOI 0408
BibRef

Petrovic, N.[Nemanja], Ivanovic, A.[Aleksandar], Jojic, N.[Nebojsa],
Recursive estimation of generative models of video,
CVPR06(I: 79-86).
IEEE DOI 0606
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Jojic, N.[Nebojsa], Petrovic, N.[Nemanja], Huang, T.S.,
Scene generative models for adaptive video fast forward,
ICIP03(II: 619-622).
IEEE DOI 0312
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Bai, S.[Song], Bai, X.[Xiang], Liu, W.,
Multiple Stage Residual Model for Image Classification and Vector Compression,
MultMed(18), No. 7, July 2016, pp. 1351-1362.
IEEE DOI 1608
data compression BibRef

Bai, S.[Song], Wang, X.G.[Xing-Gang], Yao, C.[Cong], Bai, X.[Xiang],
Multiple Stage Residual Model for Accurate Image Classification,
ACCV14(I: 430-445).
Springer DOI 1504
encoding local features. BibRef

Liang, L.M.[Lu-Ming], Wei, M.Q.[Ming-Qiang], Szymczak, A.[Andrzej], Pang, W.M.[Wai-Man], Wang, M.[Meng],
Spin Contour,
MultMed(18), No. 11, November 2016, pp. 2282-2292.
IEEE DOI 1609
feature extraction. Spin Images. BibRef

Ding, S.H.[Shou-Hong], Sheng, B.[Bin], Xie, Z.F.[Zhi-Feng], Ma, L.Z.[Li-Zhuang],
Intrinsic image estimation using near- L0 sparse optimization,
VC(33), No. 3, March 2017, pp. 355-369.
WWW Link. 1702
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Syed, S.A.[Sohaib Ali], Iqbal, M.Z.[Muhammad Zafar], Riaz, M.M.[Muhammad Mohsin],
Describing contrast across scales,
PandRS(128), No. 1, 2017, pp. 326-337.
Elsevier DOI 1706
Image descriptor. Using contrast as a feature. BibRef

Rahman, I.M.H.[Ibrahim M.H.], Hollitt, C.[Christopher], Zhang, M.J.[Meng-Jie],
Feature Map Quality Score Estimation Through Regression,
IP(27), No. 4, April 2018, pp. 1793-1808.
IEEE DOI 1802
cartography, feature extraction, image segmentation, learning (artificial intelligence), visual attention BibRef

Malu, G., Elizabeth, S.[Sherly], Koshy, S.M.[Sumod Mathew],
Circular mesh-based shape and margin descriptor for object detection,
PR(84), 2018, pp. 97-111.
Elsevier DOI 1809
Shape descriptor, Structural and global descriptor, Circular mesh-based shape and margin descriptor, Dynamic contrast enhanced magnetic resonance imaging BibRef

Pang, S.M.[Shan-Min], Xue, J.R.[Jian-Ru], Zhu, J.H.[Ji-Hua], Zhu, L.[Li], Tian, Q.[Qi],
Unifying Sum and Weighted Aggregations for Efficient Yet Effective Image Representation Computation,
IP(28), No. 2, February 2019, pp. 841-852.
IEEE DOI 1811
Feature extraction, Image representation, Image retrieval, Visualization, Standards, Task analysis, Encoding, Aggregation, image search BibRef

Klettner, S.[Silvia],
Why Shape Matters: On the Inherent Qualities of Geometric Shapes for Cartographic Representations,
IJGI(8), No. 5, 2019, pp. xx-yy.
DOI Link 1906
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Georgiou, T.[Theodoros], Liu, Y.[Yu], Chen, W.[Wei], Lew, M.[Michael],
A survey of traditional and deep learning-based feature descriptors for high dimensional data in computer vision,
MultInfoRetr(9), No. 3, September 2020, pp. 135-170.
Springer DOI 2008
Survey, Descriptions. BibRef

Baranska, A.[Anna], Bac-Bronowicz, J.[Joanna], Dejniak, D.[Dorota], Lewinski, S.[Stanislaw], Krawczyk, A.[Artur], Chrobak, T.[Tadeusz],
A Unified Methodology for the Generalisation of the Geometry of Features,
IJGI(10), No. 3, 2021, pp. xx-yy.
DOI Link 2104
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Zhang, J.[Jian], Cao, Y.Y.[Yun-Yin], Wu, Q.[Qun],
Vector of Locally and Adaptively Aggregated Descriptors for Image Feature Representation,
PR(116), 2021, pp. 107952.
Elsevier DOI 2106
VLAD, Deep learning, Weighting scheme, Gating scheme, Feature representation BibRef

Verbin, D.[Dor], Gortler, S.J.[Steven J.], Zickler, T.E.[Todd E.],
Unique Geometry and Texture From Corresponding Image Patches,
PAMI(43), No. 12, December 2021, pp. 4519-4522.
IEEE DOI 2112
Motion segmentation, Solid modeling, Transmission line matrix methods, Surface texture, structure from motion BibRef

Chakrabarti, A.[Ayan], Xiong, Y.[Ying], Gortler, S.J.[Steven J.], Zickler, T.E.[Todd E.],
Low-level vision by consensus in a spatial hierarchy of regions,
CVPR15(4009-4017)
IEEE DOI 1510
BibRef

Yu, X.H.[Xiao-Han], Gao, Y.S.[Yong-Sheng], Bennamoun, M.[Mohammed], Xiong, S.W.[Sheng-Wu],
A Lie algebra representation for efficient 2D shape classification,
PR(134), 2023, pp. 109078.
Elsevier DOI 2212
Lie algebra, 2D Shape classification, Covariance matrix, Lie group of SPD matrix BibRef

Lin, C.[Chenran], Lui, L.M.[Lok Ming],
Harmonic Beltrami Signature: A Novel 2D Shape Representation for Object Classification,
SIIMS(15), No. 4, 2022, pp. 1851-1893.
DOI Link 2212
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Pire, T.[Taihú], Gonzalez, H.[Hernán], Santano, E.[Emiliano], Terissi, L.[Lucas], Civera, J.[Javier],
An experimental evaluation of feature detectors and descriptors for visual SLAM,
IJCVR(13), No. 3, 2023, pp. 316-341.
DOI Link 2305
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Hayashi, K.[Kazuki], Tanaka, D.[Daisuke],
Effectiveness of Feature Extraction System for Multimodal Sensor Information Based on VRAE and Its Application to Object Recognition,
IEICE(E106-D), No. 5, May 2023, pp. 833-835.
WWW Link. 2305
BibRef

Feng, R.[Ruoyu], Jin, X.[Xin], Guo, Z.Y.[Zong-Yu], Feng, R.[Runsen], Gao, Y.X.[Yi-Xin], He, T.Y.[Tian-Yu], Zhang, Z.Z.[Zhi-Zheng], Sun, S.[Simeng], Chen, Z.B.[Zhi-Bo],
Image Coding for Machines with Omnipotent Feature Learning,
ECCV22(XXXVII:510-528).
Springer DOI 2211
Compress for task analysis, not human use. BibRef

Kim, J.M.[Jae Myung], Choe, J.[Junsuk], Akata, Z.[Zeynep], Oh, S.J.[Seong Joon],
Keep CALM and Improve Visual Feature Attribution,
ICCV21(8330-8340)
IEEE DOI 2203

WWW Link. Class Activation Latent Mapping. Training, Location awareness, Visualization, Codes, Computational modeling, Probabilistic logic, Recognition and classification BibRef

Zheng, Z.L.[Zi-Long], Xie, J.W.[Jian-Wen], Li, P.[Ping],
Patchwise Generative ConvNet: Training Energy-Based Models from a Single Natural Image for Internal Learning,
CVPR21(2960-2969)
IEEE DOI 2111
Training, Image recognition, Image synthesis, Computational modeling, Superresolution, Training data, Statistical distributions BibRef

Gurevich, I.[Igor], Yashina, V.[Vera],
Basic Models of Descriptive Image Analysis,
IMTA20(275-288).
Springer DOI 2103
BibRef

Guo, X.Y.[Xiao-Yang], Srivastava, A.[Anuj],
Representations, Metrics and Statistics for Shape Analysis of Elastic Graphs,
Diff-CVML20(3629-3638)
IEEE DOI 2008
For very different shapes. Shape, Measurement, Space vehicles, Feature extraction, Junctions, Topology, Tools BibRef

Misra, I.[Ishan], van der Maaten, L.[Laurens],
Self-Supervised Learning of Pretext-Invariant Representations,
CVPR20(6706-6716)
IEEE DOI 2008
Task analysis, Image representation, Semantics, Feature extraction, Visualization, Transforms, Training BibRef

Holliday, A., Dudek, G.,
Pre-trained CNNs as Visual Feature Extractors: A Broad Evaluation,
CRV20(78-84)
IEEE DOI 2006
BibRef

Genova, K., Cole, F., Vlasic, D., Sarna, A., Freeman, W., Funkhouser, T.,
Learning Shape Templates With Structured Implicit Functions,
ICCV19(7153-7163)
IEEE DOI 2004
computational geometry, image colour analysis, image representation, image segmentation, Computer architecture BibRef

Ebel, P., Trulls, E., Yi, K.M., Fua, P., Mishchuk, A.,
Beyond Cartesian Representations for Local Descriptors,
ICCV19(253-262)
IEEE DOI 2004
feature extraction, image matching, image representation, learning (artificial intelligence), object detection, Measurement BibRef

Souri, Y.[Yaser], Noury, E.[Erfan], Adeli, E.[Ehsan],
Deep Relative Attributes,
ACCV16(V: 118-133).
Springer DOI 1704
BibRef

Girdhar, R.[Rohit], Fouhey, D.F.[David F.], Rodriguez, M.[Mikel], Gupta, A.[Abhinav],
Learning a Predictable and Generative Vector Representation for Objects,
ECCV16(VI: 484-499).
Springer DOI 1611
BibRef

Toussaint, G.T.[Godfried T.], Onea, N.S.[Noris S.], Vuong, Q.H.[Quan H.],
Measuring the complexity of two-dimensional binary patterns: Sub-symmetries versus Papentin complexity,
MVA15(480-483)
IEEE DOI 1507
Complexity theory BibRef

Hadji, I.[Isma], de Souza, G.N.[Guilherme N.],
Local-to-Global Signature Descriptor for 3D Object Recognition,
RoLoD14(570-584).
Springer DOI 1504
surface point classification together with signature-based features BibRef

Liang, K.M.[Kong-Ming], Chang, H.[Hong], Cui, Z.[Zhen], Shan, S.G.[Shi-Guang], Chen, X.L.[Xi-Lin],
Representation Learning with Smooth Autoencoder,
ACCV14(II: 72-86).
Springer DOI 1504
BibRef

Xu, C.[Can], Vasconcelos, N.M.[Nuno M.],
Learning Receptive Fields for Pooling from Tensors of Feature Response,
CVPR14(835-842)
IEEE DOI 1409
image classifcation; receptive fields; tensor BibRef

Gutmann, M.U.[Michael U.], Hyvarinen, A.[Aapo],
Learning a selectivity-invariance-selectivity feature extraction architecture for images,
ICPR12(918-921).
WWW Link. 1302
What to select and what to be invariant to. BibRef

Maier, A.[Andreas],
Accelerated Centre-of-Gravity Calculation for Massive Numbers of Image Patches,
ISVC12(I: 566-574).
Springer DOI 1209
BibRef

Dragon, R.[Ralf], Shoaib, M.[Muhammad], Rosenhahn, B.[Bodo], Ostermann, J.[Joern],
NF-Features: No-Feature-Features for Representing Non-textured Regions,
ECCV10(II: 128-141).
Springer DOI 1009
Regions with no interest points. For matching and alignment.
See also HALF-SIFT: High-Accurate Localized Features for SIFT. BibRef

Knauer, U.,
Fast Computation of Region Homogeneity with Application in a Surveillance Task,
CloseRange10(xx-yy).
PDF File. 1006
BibRef

Gao, C.X.[Chang-Xin],
Evaluating the measurement scales of semantic features for remote sensing images retrieval,
CGC10(50).
PDF File. 1006
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Pires, B.R.[Bernardo Rodrigues], Moura, J.M.F.[Jose M.F.],
Shapes as empirical distributions,
ICIP09(401-404).
IEEE DOI 0911
BibRef

Matsakis, P.[Pascal],
Affine properties of the relative position PHI-descriptor,
ICPR16(1941-1946)
IEEE DOI 1705
Computational modeling, Computer science, Image color analysis, Marine vehicles, Pattern recognition, Shape, Visualization, affine transformation, invariance, relative position, spatial relationship, visual, descriptor BibRef

Matsakis, P.[Pascal], Ni, J.B.[Jing-Bo], Veltman, M.[Melanie],
Directional relationships to a reference object: A quantitative approach based on force fields,
ICIP09(321-324).
IEEE DOI 0911
Image value based on degree it satisfies a relationship to an object. BibRef