4.4 Scale Space and Multi-Scale Techniques

4.4.1 Scale Space for Descriptions

Witkin, A.P.[Andrew P.],
Scale Space Filtering: A New Approach to Multi-Scale Descriptions,
IU84(79-95). BibRef 8400
And: ICASSP84(150-153).
IEEE DOI BibRef
And:
Scale-Space Filtering,
IJCAI83(1019-1022). Reprinted in BibRef RCV87(329-332). Award, IJCAI. Filter at different resolutions and use the data from all the levels. Introduced scale space to vision. BibRef

Saund, E.,
Symbolic Construction of a 2-D Scale-Space Image,
PAMI(12), No. 8, August 1990, pp. 817-830.
IEEE DOI BibRef 9008
Earlier: MIT AI Memo-1028, April 1988, BibRef
Earlier:
Adding Scale to the Primal Sketch,
CVPR89(70-78).
IEEE DOI Generate a set of line segments at different resolutions (Scale-Space). Apply grouping techniques. BibRef

Hummel, R.,
The Scale-Space Formulation of Pyramid Data Structures,
PCV88(107-123). BibRef 8800

Dyer, C.R.,
Multiscale Image Understanding,
PCV88(171-213). BibRef 8800

Unser, M., and Eden, M.,
The L-(2) Polynomial Spline Pyramid,
PAMI(15), No. 4, April 1993, pp. 364-379.
IEEE DOI Representation, Pyramid. BibRef 9304

Dron, L.[Lisa],
The Multiscale Veto Model: A 2-Stage Analog Network for Edge-Detection and Image-Reconstruction,
IJCV(11), No. 1, August 1993, pp. 45-61.
Springer DOI BibRef 9308

Bookstein, F.L., Green, W.D.K.,
A Feature Space for Edgels in Images with Landmarks,
JMIV(3), No. 4, 1993, pp. 231-261. BibRef 9300

Johansen, P.,
On the Classification of Top Points in Scale Space,
JMIV(4), 1994, pp. 57-67. BibRef 9400

Ray, B.K., Ray, K.S.,
A New Approach to Scale-Space Image,
PRL(15), No. 4, April 1994, pp. 365-372. BibRef 9404

Pei, S.C.[Soo-Chang], Chen, F.C.[Fei-Chin],
3-D spatiotemporal subband decompositions for hierarchical compatible video coding by mathematical morphology,
SP:IC(6), No. 1, March 1994, pp. 83-99.
Elsevier DOI 0001
Subband decomposition, Video coding, Morphological filtering BibRef

Pei, S.C.[Soo-Chang], Chen, F.C.[Fei-Chin],
Hierarchical Image Representation by Mathematical Morphology Sub-Band Decomposition,
PRL(16), No. 2, February 1995, pp. 183-192. BibRef 9502

Bijaoui, A., Rue, F.,
A Multiscale Vision Model Adapted to the Astronomical Images,
SP(46), No. 3, October 1995, pp. 345-362. BibRef 9510

Ahuja, N.,
On Detection and Representation of Multiscale Low-Level Image Structure,
Surveys(27), No. 3, September 1995, pp. 304-306. Survey, Scale-Space. BibRef 9509

Soille, P., and Rivest, J.F.,
On the Validity of Fractal Dimension Measurements in Image Analysis,
JVCIR(7), 1996, pp. 217-229. BibRef 9600

Rivest, J.F., Serra, J., Soille, P.,
Dimensionality in Image Analysis,
JVCIR(3), 1992, pp. 137-146. BibRef 9200

Dudek, G.[Gregory],
Shape Description and Classification Using the Interrelationship of Structures at Multiple Scales,
MDSG94(473-492). BibRef 9400
And:
Shape Metrics from Curvature-Scale Space and Curvature-Tuned Smoothing,
SPIE(1570), 1991, pp. 75-85. BibRef

Hong, L., Cao, J., Chen, G.R.,
A Multiresolutional Approach to 3D Object Recognition,
CSSP(16), No. 2, 1997, pp. 217-239. 9703
BibRef

Griffin, L.D.[Lewis D.],
Scale-Imprecision Space,
IVC(15), No. 5, May 1997, pp. 369-398.
Elsevier DOI 9706
BibRef

Cong, G.[Ge], Ma, S.D.[Song De],
Dyadic Scale-Space,
PR(30), No. 2, February 1997, pp. 339-352. 9704
BibRef
Earlier:
Elsevier DOI ICPR96(II: 399-402).
IEEE DOI 9608
(Chinese Academy of Sciences, PRC) BibRef

Cong, G.[Ge], Ma, S.D.[Song De],
Corner Enhancement in Curvature Scale Space,
PR(31), No. 10, October 1998, pp. 1491-1501.
Elsevier DOI 9808
BibRef

Guichard, F.,
A Morphological, Affine, and Galilean Invariant Scale-Space for Movies,
IP(7), No. 3, March 1998, pp. 444-456.
IEEE DOI 9803
BibRef

Solina, F.[Franc], Leonardis, A.[Aleš],
Proper Scale for Modeling Visual Data,
IVC(16), No. 2, February 20 1998, pp. 89-98.
Elsevier DOI 9803
BibRef

Chellappa, R., Girod, B., Munson, D.C., Tekalp, M., Vetterli, M.,
The Past, Present, and Future of Image and Multidimensional Signal-Processing,
SPMag(15), No. 2, March 1998, pp. 21-58. 9804
BibRef

Fdez Valdivia, J., Garcia, J.A., Martinez Baena, J., Fdez Vidal, X.R.[Xose R.],
The Selection of Natural Scales in 2D Images Using Adaptive Gabor Filtering,
PAMI(20), No. 5, May 1998, pp. 458-469.
IEEE DOI 9806
BibRef

Martinez Baena, J., Garcia, J.A., Fdez Valdivia, J., Rodriguez Sanchez, R.,
Scale Selection Using 3 Different Representations For Images,
PRL(18), No. 14, December 1997, pp. 1453-1467. 9806
BibRef
Earlier: A2, A3, A1, Only:
Scale Selection Using Three Different Representations for Images,
ScaleSpace97(xx). 9702
BibRef

Combettes, P.L.[Patrick L.],
Convex Set-Theoretic Image Recovery by Extrapolated Iterations of Parallel Subgradient Projections,
IP(6), No. 4, April 1997, pp. 493-506.
IEEE DOI 9704
BibRef
Earlier:
Generalized convex set theoretic image recovery,
ICIP96(II: 453-456).
IEEE DOI BibRef
Earlier:
Convex set theoretic image recovery via chaotic iterations of approximate projections,
ICIP94(III: 182-186).
IEEE DOI 9411
BibRef

Combettes, P.L.,
Convex Set Theoretic Image Recovery with Inexact Projection Algorithms,
ICIP01(I: 257-260).
IEEE DOI 0108
BibRef

Combettes, P.L.[Patrick L.],
On the Numerical Robustness of the Parallel Projection Method in Signal Synthesis,
SPLetters(8), No. 2, February 2001, pp. 45-47.
IEEE Top Reference. 0101
BibRef
Earlier:
A Surrogate Projection Method for the Constrained Minimization of Residual Energy in Image Restoration,
ICIP99(25PO4). Not in proceedings. BibRef

Combettes, P.L.[Patrick L.], Pesquet, J.C.,
Convex Multiresolution Analysis,
PAMI(20), No. 12, December 1998, pp. 1308-1318.
IEEE DOI BibRef 9812
Earlier:
Nonlinear multiresolution image analysis via convex projections,
ICIP98(II: 762-765).
IEEE DOI 9810
Extension of wavelet analysis. BibRef

Combettes, P.L.[Patrick L.], Glaudin, L.E.[Lilian E.],
Proximal Activation of Smooth Functions in Splitting Algorithms for Convex Image Recovery,
SIIMS(12), No. 4, 2019, pp. 1905-1935.
DOI Link 1912
BibRef

Tapamo, J.R.[Jules-Raymond],
Multi-Scale Image Analysis by Pyramidal Algorithms,
JMIV(10), No. 1, January 1999, pp. 87-95.
DOI Link BibRef 9901

García Salinas, M.J.[María José], Gomez Lopera, J.F.[Juan Francisco], Luque Escamilla, P.L.[Pedro Luis], Martinez Aroza, J.[José], Román Roldán, R.[Ramón], Segura Luna, J.C.[J. Carlos],
Empirical multiresolution models applicable to gray-level image processing,
SP:IC(11), No. 2, December 1997, pp. 83-93.
Elsevier DOI BibRef 9712

Chen, C.C.[Chi-Chyang], Wang, C.D.[Chiou-Dong],
A simple edge-preserving filtering technique for constructing multi-resolution systems of images,
PRL(20), No. 5, May 1999, pp. 495-506. 9912
BibRef

Faugeras, O.D.[Olivier D.], Nielsen, M.[Mads], Perona, P.[Pietro], ter Haar Romeny, B.M.[Bart M.], Sapiro, G.[Guillermo],
Special Issue on the Second International Conference on Scale Space Theory in Computer Vision, Guest Editors' Comments,
JVCIR(11), No. 2, June 2000, pp. 95-95. 0008
BibRef

Goutsias, J., Heijmans, H.J.A.M.,
Nonlinear Multiresolution Signal Decomposition Schemes--Part I: Morphological Pyramids,
IP(9), No. 11, November 2000, pp. 1862-1876.
IEEE DOI 0011

See also Nonlinear Multiresolution Signal Decomposition Schemes--Part II: Morphological Wavelets. BibRef

Kadir, T.[Timor], Brady, M.[Michael],
Saliency, Scale and Image Description,
IJCV(45), No. 2, November 2001, pp. 83-105.
DOI Link 0111
A multiscale algorithm for the selection of salient regions of an image, applied to tracking, recognition and retrieval.
See also Comparison of Affine Region Detectors, A. BibRef

Kadir, T.[Timor], Brady, M.[Michael],
Estimating statistics in arbitrary regions of interest,
BMVC05(xx-yy).
HTML Version. 0509
BibRef

Joshi, N., Kadir, T., Brady, S.M.,
Simplified Computation for Nonparametric Windows Method of Probability Density Function Estimation,
PAMI(33), No. 8, August 2011, pp. 1673-1680.
IEEE DOI 1107
BibRef

Kadir, T., Brady, M.,
Unsupervised non-parametric region segmentation using level sets,
ICCV03(1267-1274).
IEEE DOI 0311
BibRef

Raducanu, B.[Bogdan], Graña, M.[Manuel], Albizuri, F.X.[F. Xabier],
Morphological Scale Spaces and Associative Morphological Memories: Results on Robustness and Practical Applications,
JMIV(19), No. 2, September 2003, pp. 113-131.
DOI Link 0308
BibRef

Saha, P.K.[Punam Kumar],
Tensor scale: A local morphometric parameter with applications to computer vision and image processing,
CVIU(99), No. 3, September 2005, pp. 384-413.
Elsevier DOI 0508
Localized scale. For matching slices. BibRef

Xu, Z.Y.[Zi-Yue], Saha, P.K.[Punam K.], Dasgupta, S.[Soura],
Tensor scale: An analytic approach with efficient computation and applications,
CVIU(116), No. 10, October 2012, pp. 1060-1075.
Elsevier DOI 1209
Scale-space, Local scale, Morphometry, Tensor scale, Image filtering; Image interpolation BibRef

Saha, P.K.[Punam K.], Xu, Z.Y.[Zi-Yue],
An Analytic Approach to Tensor Scale with an Efficient Algorithm and Applications to Image Filtering,
DICTA10(429-434).
IEEE DOI 1012
BibRef

Ghosh, K.[Kuntal], Sarkar, S.[Sandip], Bhaumik, K.[Kamales],
Understanding image structure from a new multi-scale representation of higher order derivative filters,
IVC(25), No. 8, 1 August 2007, pp. 1228-1238.
Elsevier DOI 0706
Multi-scale filters, Derivative filters, Zero-crossings; Non-classical receptive field BibRef

Markussen, B.[Bo], Steenstrup Pedersen, K.[Kim], Loog, M.[Marco],
Second Order Structure of Scale-Space Measurements,
JMIV(31), No. 2-3, July 2008, pp. 207-220.
WWW Link. 0711
BibRef
Earlier: A2, A3, A1:
Generic Maximum Likely Scale Selection,
SSVM07(362-373).
Springer DOI 0705
BibRef

Wang, Y.Z.[Yi-Zhou], Zhu, S.C.[Song-Chun],
Perceptual Scale-Space and Its Applications,
IJCV(80), No. 1, October 2008, pp. xx-yy.
Springer DOI 0809
BibRef
Earlier: Add A2: Bahrami, S.[Siavosh], ICCV05(I: 58-65).
IEEE DOI 0510
BibRef

Gilboa, G.[Guy],
Nonlinear Scale Space with Spatially Varying Stopping Time,
PAMI(30), No. 12, December 2008, pp. 2175-2187.
IEEE DOI 0811
Applied to denoising signals.
See also Variational Denoising of Partly Textured Images by Spatially Varying Constraints.
See also Structure-Texture Image Decomposition: Modeling, Algorithms, and Parameter Selection. BibRef

Vanhamel, I.[Iris], Mihai, C.[Cosmin], Sahli, H.[Hichem], Katartzis, A.[Antonis], Pratikakis, I.E.[Ioannis E.],
Scale Selection for Compact Scale-Space Representation of Vector-Valued Images,
IJCV(84), No. 2, August 2009, pp. xx-yy.
Springer DOI 0906
BibRef
Earlier: A2, A1, A3, A4, A5: SSVM07(32-42).
Springer DOI 0705
BibRef

Yang, Z.W.[Zheng-Wu], Fang, T.[Tao],
On the accuracy of image normalization by Zernike moments,
IVC(28), No. 3, March 2010, pp. 403-413.
Elsevier DOI 1001
Image normalization, Zernike moments, Image regularization, Scale space BibRef

Chen, W.R.[Wei-Rong], Henebry, G.M.[Geoffrey M.],
Change of spatial information under rescaling: A case study using multi-resolution image series,
PandRS(64), No. 6, November 2009, pp. 592-597.
Elsevier DOI 1001
High spatial resolution imagery, Semivariogram analysis, Spatial structure, Rescaling BibRef

Tadmor, E.[Eitan], Athavale, P.[Prashant],
Multiscale Image Representation Using Novel Integro-Differential Equations,
IPI(3), 2009, pp. 693-710. BibRef 0900

Athavale, P.[Prashant], Tadmor, E.[Eitan],
Integro-Differential Equations Based On (BV, L^1) Image Decomposition,
SIIMS(4), No. 1, 2011, pp. 300-312.
DOI Link 1106
hierarchical image decompositions, total variation, denoising; deblurring, inverse scale, variational problem, integro-differential equation, energy decomposition BibRef

Bariya, P.[Prabin], Novatnack, J.[John], Schwartz, G.[Gabriel], Nishino, K.[Ko],
3D Geometric Scale Variability in Range Images: Features and Descriptors,
IJCV(99), No. 2, September 2012, pp. 232-255.
Springer DOI 1205
Range image, Scale variability, Scale-space, Geometric feature, Shape descriptor, Range image registration, 3D object recognition. Variations is spatial extents of local structures of 3D data. BibRef

Bariya, P.[Prabin], Nishino, K.[Ko],
Scale-hierarchical 3D object recognition in cluttered scenes,
CVPR10(1657-1664).
IEEE DOI 1006
Scale variability of local structure. BibRef

Novatnack, J.[John], Nishino, K.[Ko],
Scale-Dependent 3D Geometric Features,
ICCV07(1-8).
IEEE DOI 0710
BibRef

Novatnack, J.[John], Nishino, K.[Ko], Shokoufandeh, A.[Ali],
Extracting 3D Shape Features in Discrete Scale-Space,
3DPVT06(946-953).
IEEE DOI 0606
BibRef

Zaharescu, A.[Andrei], Boyer, E.[Edmond], Horaud, R.[Radu],
Keypoints and Local Descriptors of Scalar Functions on 2D Manifolds,
IJCV(100), No. 1, October 2012, pp. 78-98.
WWW Link. 1208
BibRef
Earlier:
Scale-space representation of scalar functions on 2D manifolds,
3DRR11(609-616).
IEEE DOI 1201
BibRef

Elfiky, N.M.[Noha M.], Gonzàlez, J.[Jordi], Roca, F.X.[F. Xavier],
Compact and adaptive spatial pyramids for scene recognition,
IVC(30), No. 8, August 2012, pp. 492-500.
Elsevier DOI 1209
Scene recognition, Spatial pyramids, Texture, Dimensionality reduction; Agglomerative information theory BibRef

Elfiky, N.M.[Noha M.], Khan, F.S.[Fahad Shahbaz], van de Weijer, J.[Joost], Gonzàlez, J.[Jordi],
Discriminative compact pyramids for object and scene recognition,
PR(45), No. 4, 2012, pp. 1627-1636.
Elsevier DOI 1410
Object and scene recognition BibRef

Vondenhoff, E.,
Uniqueness Results for Image Reconstruction from Features on Curves in alpha-Scale Spaces,
JMIV(45), No. 1, January 2013, pp. 1-12.
WWW Link. 1301
2-D image specified by features on 3-D curves BibRef

Theriault, C.[Christian], Thome, N.[Nicolas], Cord, M.[Matthieu],
Extended Coding and Pooling in the HMAX Model,
IP(22), No. 2, February 2013, pp. 764-777.
IEEE DOI 1302
BibRef
Earlier:
HMAX-S: Deep scale representation for biologically inspired image categorization,
ICIP11(1261-1264).
IEEE DOI 1201
BibRef

Theriault, C.[Christian], Thome, N.[Nicolas], Cord, M.[Matthieu],
Dynamic Scene Classification: Learning Motion Descriptors with Slow Features Analysis,
CVPR13(2603-2610)
IEEE DOI 1309
Motion descriptors BibRef

Li, J.[Jian], Levine, M.D.[Martin D.], An, X.J.[Xiang-Jing], Xu, X.[Xin], He, H.[Hangen],
Visual Saliency Based on Scale-Space Analysis in the Frequency Domain,
PAMI(35), No. 4, April 2013, pp. 996-1010.
IEEE DOI 1303
BibRef
Earlier: A1, A2, A3, A5, Only:
Saliency Detection Based on Frequency and Spatial Domain Analyses,
BMVC11(xx-yy).
HTML Version. 1110
Detect large and small, inhibit repetitive.
See also Real-Time Long-Range Lane Detection and Tracking for Intelligent Vehicle. BibRef

Mu, N.[Nan], Xu, X.[Xin], Zhang, X.L.[Xiao-Long], Lin, X.L.[Xiao-Li],
Discrete stationary wavelet transform based saliency information fusion from frequency and spatial domain in low contrast images,
PRL(115), 2018, pp. 84-91.
Elsevier DOI 1812
Frequency domain, Spatial domain, Saliency detection, Discrete stationary wavelet transform, Low contrast image BibRef

Mu, N.[Nan], Xu, X.[Xin], Zhang, X.L.[Xiao-Long],
A spatial-frequency-temporal domain based saliency model for low contrast video sequences,
JVCIR(58), 2019, pp. 79-88.
Elsevier DOI 1901
Salient object detection, Low contrast videos, Multimodal fusion, Region covariance, Incremental learning BibRef

Bates, J.[Jonathan], Mio, W.[Washington],
Density Estimators of Gaussian Type on Closed Riemannian Manifolds,
JMIV(50), No. 1-2, September 2014, pp. 53-59.
WWW Link. 1408
BibRef

Bates, J.[Jonathan], Liu, X.W.[Xiu-Wen], Mio, W.[Washington],
Scale-Space Spectral Representation of Shape,
ICPR10(2648-2651).
IEEE DOI 1008
BibRef

Tschirsich, M.[Martin], Kuijper, A.[Arjan],
Notes on Discrete Gaussian Scale Space,
JMIV(51), No. 1, January 2015, pp. 106-123.
WWW Link. 1503
BibRef
Earlier:
Discrete Deep Structure,
SSVM13(343-354).
Springer DOI 1305
BibRef
Earlier:
A Discrete Scale Space Neighborhood for Robust Deep Structure Extraction,
SSSPR12(126-134).
Springer DOI 1211
BibRef
And:
Laplacian Eigenimages in Discrete Scale Space,
SSSPR12(162-170).
Springer DOI 1211
BibRef

Jiang, B.[Bin], Brandt, S.A.[S. Anders],
A Fractal Perspective on Scale in Geography,
IJGI(5), No. 6, 2016, pp. 95.
DOI Link 1608
BibRef

Liang, W.J.[Wei-Jie], Lin, G.X.[Gang-Xuan], Lu, C.S.[Chun-Shien],
Tree Structure Sparsity Pattern Guided Convex Optimization for Compressive Sensing of Large-Scale Images,
IP(26), No. 2, February 2017, pp. 847-859.
IEEE DOI 1702
compressed sensing BibRef

Calatroni, L.[Luca], van Gennip, Y.[Yves], Schönlieb, C.B.[Carola-Bibiane], Rowland, H.M.[Hannah M.], Flenner, A.[Arjuna],
Graph Clustering, Variational Image Segmentation Methods and Hough Transform Scale Detection for Object Measurement in Images,
JMIV(57), No. 2, February 2017, pp. 269-291.
Springer DOI 1702
Scale detection. BibRef

Hu, Z.W.[Zhong-Wen], Li, Q.Q.[Qing-Quan], Zhang, Q.[Qian], Zou, Q.[Qin], Wu, Z.C.[Zhao-Cong],
Unsupervised Simplification of Image Hierarchies via Evolution Analysis in Scale-Sets Framework,
IP(26), No. 5, May 2017, pp. 2394-2407.
IEEE DOI 1704
Clustering algorithms BibRef

Ben Khlifa, A.[Ameni], Ghorbel, F.[Faouzi],
An almost complete curvature scale space representation: Euclidean case,
SP:IC(75), 2019, pp. 32-43.
Elsevier DOI 1906
Curvature Scale Space, Almost-completeness, Curvature's levels, Shape recognition, Retrieval BibRef

Wong, F.[Fukoeng], Hu, H.F.[Hai-Feng],
Adaptive learning feature pyramid for object detection,
IET-CV(13), No. 8, December 2019, pp. 742-748.
DOI Link 1912
More consistent detection at different scales. BibRef

Razzaghi, P.[Parvin], Abbasi, K.[Karim], Bayat, P.[Pegah],
Learning spatial hierarchies of high-level features in deep neural network,
JVCIR(70), 2020, pp. 102817.
Elsevier DOI 2007
Perceptual grouping, Modified Guided Co-occurrence Block (mGCoB), Spatial hierarchies of high-level features BibRef

Gao, S.H.[Shang-Hua], Cheng, M.M.[Ming-Ming], Zhao, K.[Kai], Zhang, X.Y.[Xin-Yu], Yang, M.H.[Ming-Hsuan], Torr, P.H.S.[Philip H.S.],
Res2Net: A New Multi-Scale Backbone Architecture,
PAMI(43), No. 2, February 2021, pp. 652-662.
IEEE DOI 2101
Feature extraction, Task analysis, Object detection, Semantics, Kernel, Convolution, Multi-scale, deep learning BibRef

Pintea, S.L.[Silvia L.], Tömen, N.[Nergis], Goes, S.F.[Stanley F.], Loog, M.[Marco], van Gemert, J.C.[Jan C.],
Resolution Learning in Deep Convolutional Networks Using Scale-Space Theory,
IP(30), 2021, pp. 8342-8353.
IEEE DOI 2110
Shape, Spatial resolution, Taylor series, Kernel, Standards, Network architecture, Wavelet transforms, Scale-space theory, resolution learning in deep networks BibRef

Ruan, Z.L.[Zhong-Ling], Wang, H.[Hao], Cao, J.Z.[Jian-Zhong], Zhang, H.B.[Hong-Bo],
Cross-scale feature fusion connection for a YOLO detector,
IET-CV(16), No. 2, 2022, pp. 99-110.
DOI Link 2202
image processing, object detection BibRef

Xi, X.[Xing], Wu, Y.Q.[Yuan-Qing], Xia, C.M.[Can-Ming], He, S.H.[Sheng-Huang],
Feature fusion for object detection at one map,
IVC(123), 2022, pp. 104466.
Elsevier DOI 2206
Object detection, Multi-scale fusion, COCO BibRef

Xie, J.[Jiyang], Su, X.[Xiu], You, S.[Shan], Ma, Z.Y.[Zhan-Yu], Wang, F.[Fei], Qian, C.[Chen],
ScaleNet: Searching for the Model to Scale,
ECCV22(XXI:104-120).
Springer DOI 2211

WWW Link. BibRef

Sun, R.[Ran], Chen, G.[Gaojie], Ma, J.[Jie], An, P.[Pei],
Straight Sampling Network for Point Cloud Learning,
ICIP21(3088-3092)
IEEE DOI 2201
Hierarchical Framework. Training, Cloud computing, Shape, Image processing, Gaussian noise, Straight Sampling, Straight Through Estimator, Point Cloud, BibRef

Xie, J.H.[Jia-Hao], Zhang, S.[Sheng], Lu, J.W.[Jian-Wei], Luo, Y.[Ye],
L-Snet: from Region Localization To Scale Invariant Medical Image Segmentation,
ICIP21(41-45)
IEEE DOI 2201
Scale. Location awareness, Training, Image segmentation, Computational modeling, anchor free detection BibRef

Nematzadeh, N.[Nasim], Powers, D.[David], Lewis, T.[Trent],
Vis-CRF: A Simplified Filtering Model for Vision,
DICTA20(1-8)
IEEE DOI 2201
Radio frequency, Visualization, Filtering, Computational modeling, Image edge detection, Biological system modeling, Retina, Pattern recognition BibRef

Qiao, Z.N.[Zhi-Nan], Yuan, X.H.[Xiao-Hui], Zhuang, C.Y.[Cheng-Yuan], Meyarian, A.[Abolfazl],
Attention Pyramid Module for Scene Recognition,
ICPR21(7521-7528)
IEEE DOI 2105
Code, Recognition.
WWW Link. Vocabulary, Image recognition, Semantics, Pipelines, Benchmark testing, Streaming media, feature pyramid BibRef

Zhang, D.[Dong], Zhang, H.W.[Han-Wang], Tang, J.H.[Jin-Hui], Wang, M.[Meng], Hua, X.S.[Xian-Sheng], Sun, Q.R.[Qian-Ru],
Feature Pyramid Transformer,
ECCV20(XXVIII:323-339).
Springer DOI 2011
BibRef

Cárdenas, M.[Marcelo], Peter, P.[Pascal], Weickert, J.[Joachim],
Sparsification Scale-Spaces,
SSVM19(303-314).
Springer DOI 1909
BibRef

Zhou, P.[Peng], Ni, B.B.[Bing-Bing], Geng, C.[Cong], Hu, J.G.[Jian-Guo], Xu, Y.[Yi],
Scale-Transferrable Object Detection,
CVPR18(528-537)
IEEE DOI 1812
Feature extraction, Object detection, Semantics, Detectors, Image resolution, Convolution, Heart BibRef

Ramos, L.A.[Lucas Alexandre], Marana, A.N.[Aparecido Nilceu], de Souza, Jr., L.A.[Luis Antônio],
A Scale-Space Approach for Multiscale Shape Analysis,
CIARP17(542-549).
Springer DOI 1802
BibRef

Rampal, K., Sakurai, K., Imaoka, H.,
Fast and accurate scale estimation method for object tracking,
ICPR16(2712-2715)
IEEE DOI 1705
Decision support systems, Feature extraction, Kernel, Maximum likelihood estimation, Object tracking, object tracking, scale, estimation BibRef

Scalzo-Cornacchia, M.[Maria], Velipasalar, S.[Senem],
Scale estimation with difference of ordered residuals,
ICIP15(3377-3381)
IEEE DOI 1512
BibRef

Liu, X.M.[Xian-Ming], Ji, R.R.[Rong-Rong], Wang, C.H.[Chang-Hu], Liu, W.[Wei], Zhong, B.N.[Bi-Neng], Huang, T.S.[Thomas S.],
Understanding image structure via hierarchical shape parsing,
CVPR15(5042-5050)
IEEE DOI 1510
BibRef

Alves, W.A.L.[Wonder A. L.], Morimitsu, A.[Alexandre], Hashimoto, R.F.[Ronaldo F.],
Scale-Space Representation Based on Levelings Through Hierarchies of Level Sets,
ISMM15(265-276).
Springer DOI 1506
BibRef

Cárdenas, G.M.[Giovanno Marcelo], Weickert, J.[Joachim], Schäffer, S.[Sarah],
A Linear Scale-Space Theory for Continuous Nonlocal Evolutions,
SSVM15(103-114).
Springer DOI 1506
BibRef

Serra, J.[Jean], Kiran, B.R.[Bangalore Ravi],
Energetic lattice for optimizing over hierarchies of partitions,
ICIP14(4857-4861)
IEEE DOI 1502
Convergence BibRef

Rocca, L.[Luigi], Puppo, E.[Enrico],
A Virtually Continuous Representation of the Deep Structure of Scale-Space,
CIAP13(II:522-531).
Springer DOI 1309
BibRef

Fleischmann, O.[Oliver], Sommer, G.[Gerald],
Automatic Scale Selection of Superimposed Signals,
DAGM12(297-306).
Springer DOI 1209
BibRef

Ni, B.B.[Bing-Bing], Xu, M.D.[Meng-Di], Tang, J.H.[Jin-Hui], Yan, S.C.[Shui-Cheng], Moulin, P.[Pierre],
Omni-range spatial contexts for visual classification,
CVPR12(3514-3521).
IEEE DOI 1208
Size changes. BibRef

Chen, C.[Chao], Edelsbrunner, H.[Herbert],
Diffusion runs low on persistence fast,
ICCV11(423-430).
IEEE DOI 1201
BibRef

Hidane, M., Lézoray, O.[Olivier], El Moataz, A.,
A scale-space based hierarchical representation of discrete data,
ICIP11(285-288).
IEEE DOI 1201
BibRef

Yang, J.[Jimei], Safar, S.[Simon], Yang, M.H.[Ming-Hsuan],
Max-Margin Boltzmann Machines for Object Segmentation,
CVPR14(320-327)
IEEE DOI 1409
Boltzmann Machines BibRef

Tsai, Y.H.[Yi-Hsuan], Yang, J.[Jimei], Yang, M.H.[Ming-Hsuan],
Decomposed Learning for Joint Segmentation and Categorization,
BMVC13(xx-yy).
DOI Link 1402
BibRef
And: A2, A3, Only:
Learning Hierarchical Image Representation with Sparsity, Saliency and Locality,
BMVC11(xx-yy).
HTML Version. 1110

See also Learning structured visual dictionary for object tracking. BibRef

Karla, J.W.[Jason W.], Lalibertea, A.S.[Andrea S.], Rangoa, A.[Albert],
Spatial Dependence of Predictions from Image Segmentation: A Methods to Determine Appropriate Scales for Producing Land-Management Information,
GEOBIA10(xx-yy).
PDF File. 1007
BibRef

Paris, S.[Sebastien], Glotin, H.[Herve],
Pyramidal Multi-level Features for the Robot Vision@ICPR 2010 Challenge,
ICPR10(2949-2952).
IEEE DOI 1008
2 hierarchical features. BibRef

Li, H.[Hao], Peng, Y.X.[Yu-Xin],
Effective Multi-level Image Representation for Image Categorization,
ICPR10(1048-1051).
IEEE DOI 1008
BibRef

Dai, D.X.[Deng-Xin], Yang, W.[Wen], Wu, T.F.[Tian-Fu],
Three-layer Spatial Sparse Coding for Image Classification,
ICPR10(613-616).
IEEE DOI 1008
BibRef

Nilufar, S.[Sharmin], Ray, N.[Nilanjan], Zhang, H.[Hong],
Object Detection With DoG Scale-Space: A Multiple Kernel Learning Approach,
IP(21), No. 8, August 2012, pp. 3744-3756.
IEEE DOI 1208
BibRef
And:
Wavelet subband-based steam detection by multiple kernel learning,
ICIP12(1153-1156).
IEEE DOI 1302
BibRef
Earlier:
Optimum kernel function design from scale space features for object detection,
ICIP09(861-864).
IEEE DOI 0911
BibRef

Brill, M.H.,
Visual adaptation of scale and imprecision in a noisy world,
AIPR04(28-32).
IEEE DOI 0410
BibRef

Hirano, Y.[Yuta], Imiya, A.[Atsushi],
Scale-Space Clustering on a Unit Hypersphere,
CAIP15(I:186-197).
Springer DOI 1511
BibRef

Sakai, T.[Tomoya], Nishiguchi, H.[Haruhiko], Itoh, H.[Hayato], Imiya, A.[Atsushi],
Bifurcation of Segment Edge Curves in Scale Space,
SSVM11(302-313).
Springer DOI 1201
BibRef
Earlier: A2, A4, A1, Only:
Scale Space Hierarchy of Segments,
CAIP09(947-954).
Springer DOI 0909
BibRef

Bileschi, S.[Stanley],
Object detection at multiple scales improves accuracy,
ICPR08(1-5).
IEEE DOI 0812
BibRef

Wu, Q.[Qing], Chen, C.[Chun], Yu, Y.Z.[Yi-Zhou],
Wavelet-based hybrid multilinear models for multidimensional image approximation,
ICIP08(2828-2831).
IEEE DOI 0810
BibRef

Wu, Q.[Qing], Xia, T.[Tian], Yu, Y.Z.[Yi-Zhou],
Hierarchical Tensor Approximation of Multidimensional Images,
ICIP07(IV: 49-52).
IEEE DOI 0709
Transform into set of signals to capture multi-scale structures. BibRef

Derpanis, K.G.P.[Konstantinos G.P.], Leung, E.T.H.[Erich T. H.], Sizintsev, M.[Mikhail],
Fast Scale-Space Feature Representations by Generalized Integral Images,
ICIP07(IV: 521-524).
IEEE DOI 0709
BibRef

Unnikrishnan, R., Hebert, M.,
Denoising Manifold and Non-Manifold Point Clouds,
BMVC07(xx-yy).
PDF File. 0709
BibRef

Lalonde, J.F., Unnikrishnan, R., Vandapel, N., Hebert, M.,
Scale selection for classification of point-sampled 3D surfaces,
3DIM05(285-292).
IEEE DOI 0508
BibRef
And: CMU-RI-TR-05-01, January, 2005.
WWW Link. BibRef

Unnikrishnan, R.[Ranjith], Lalonde, J.F.[Jean-Francois], Vandapel, N.[Nicolas], Hebert, M.[Martial],
Scale Selection for the Analysis of Point-Sampled Curves,
3DPVT06(1026-1033).
IEEE DOI 0606
BibRef
And:
Scale Selection for the Analysis of Point Sampled Curves: Extended Report,
CMU-RI-TR-06-25, June, 2006.
WWW Link. BibRef

Chattopadhyay, S., Bhandarkar, S.M.,
MMR: Mask Based Multi-Resolution Images and Videos,
ICIP06(2149-2152).
IEEE DOI 0610
BibRef

Makrogiannis, S.[Sokratis], Bourbakis, N.G.[Nikolaos G.],
Localization Scale Selection for Scale-Space Segmentation,
ICIAR05(1-8).
Springer DOI 0509
BibRef

Grazzini, J., Turiel, A., Yahia, H.,
Entropy estimation and multiscale processing in meteorological satellite images,
ICPR02(III: 764-767).
IEEE DOI 0211
BibRef

Comic, L.[Lidija], Mesmoudi, M.M.[Mohammed Mostefa], de Floriani, L.[Leila],
Smale-Like Decomposition and Forman Theory for Discrete Scalar Fields,
DGCI11(477-488).
Springer DOI 1104
BibRef

de Floriani, L.[Leila], Mesmoudi, M.M.[Mohammed Mostefa], Danovaro, E.,
A smale-like decomposition for discrete scalar fields,
ICPR02(I: 184-187).
IEEE DOI 0211
BibRef

Mühlich, M.[Matthias], Mester, R.[Rudolf],
Subspace Methods and Equilibration in Computer Vision,
SCIA01(O-Tu4B). 0206
BibRef

Chomat, O., de Verdiere, V.C.[V. Colin], Hall, D., Crowley, J.L.,
Local Scale Selection for Gaussian Based Description Techniques,
ECCV00(I: 117-134).
Springer DOI 0003
BibRef

Ranjan, U.S.[Uma S.], Ramakrishnan, K.R.,
A Stochastic Scale Space for Multiscale Image Representation,
ScaleSpace99(441-446). BibRef 9900

Winter, A., Maitre, H., Cambou, N., and Legrand, E.,
An Original Multi-Sensor Approach to Scale-Based Image Analysis for Aerial and Satellite Images,
ICIP97(II: 234-237).
IEEE DOI BibRef 9700

Baldwin, B.[Bernard], Geiger, D.[Davi], and Hummel, R.A.[Robert A.],
Resolution-Appropriate Shape Representation,
ICCV98(460-465).
IEEE DOI BibRef 9800

Zekri, E.[Eric],
On Shape Recovery from Scale-Space Moments on Untextured Surfaces,
SCIA97(xx-yy)
HTML Version. 9705
BibRef

Berkner, K.[Kathrin],
Reconstruction of Self-Similar Functions from Scale-Space,
ScaleSpace97(xx). 9702
BibRef

Aviad, Z.,
A Discrete Scale-Space Representation,
ICCV87(417-421). BibRef 8700

Sporring, J.[Jon], Weickert, J.A.,
On Generalized Entropies and Scale-Space,
ScaleSpace97(xx). 9702
BibRef

Sporring, J.,
The Entropy of Scale-Space,
ICPR96(I: 900-904).
IEEE DOI 9608
(Kobenhavns Univ. DK) BibRef

Cesar, Jr., R.M.[Roberto Marcondes], da Fontoura Costa, L.[Luciano],
Shape Characterization in Natural Scales By Using the Multiscale Bending Energy,
ICPR96(I: 735-739).
IEEE DOI 9608
(IFSC, Univ. of Sao Paulo, BR) BibRef

Chinveeraphan, S., Takamatsu, R., Sato, M.,
A Hierarchical Description of Digital Grayscale Images Based on Image Dipoles,
ICPR96(II: 246-250).
IEEE DOI 9608
(Tokyo Institute of Technology, J) BibRef

Kin, G., Sato, M.,
Scale space filtering on spherical pattern,
ICPR92(III:638-641).
IEEE DOI 9208
BibRef

Bertolino, P.[Pascal], Montanvert, A.,
Multiresolution Segmentation Using the Irregular Pyramid,
ICIP96(I: 257-260).
IEEE DOI BibRef 9600

Simon, B.[Benoit], Mertes, J.Y., Ciblat, P., Macq, B.,
Local Interpolation in Multiresolution Decomposition of Images,
ICIP96(I: 287-290).
IEEE DOI BibRef 9600

Zhao, D., Zhang, X.,
Morphological Multiscale Representation for Boundaries and Surfaces,
SCV95(139-144).
IEEE DOI University of Michigan-Dearborn. MST -- morphological scale transform -- for descriptions. BibRef 9500

Jagersand, M.[Martin],
A Scale Decomposed Information Measure in Images,
ARPA94(I:717-724). BibRef 9400

Geiger, D., and Kogler, Jr., J.E.,
Scaling Images and Image Features via the Renormalization Group,
CVPR93(47-53).
IEEE DOI BibRef 9300

Kimia, B.B., Tannenbaum, A., Zucker, S.W.,
Entropy Scale-Space,
VF91(333-344). BibRef 9100

Wada, T., and Sato, M.,
Scale-Space Tree and Its Hierarchy,
ICPR90(II: 103-108).
IEEE DOI BibRef 9000

Lacroix, V.,
The primary raster: a multiresolution image description,
ICPR90(I: 903-907).
IEEE DOI 9006
BibRef

Zhuang, C.,
Scale-Based Hierarchical Description and Matching of Waveforms,
ICPR88(II: 1268-1270).
IEEE DOI BibRef 8800

Chapter on Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar continues in
Scale Space Computation of Features .