article

2D and 3D shape retrieval using skeleton filling rate

Authors:

M. Fatih DemirciAuthors Info & Claims

Multimedia Tools and Applications, Volume 76, Issue 6

Pages 7823 - 7848

https://doi.org/10.1007/s11042-016-3422-2

Published: 01 March 2017 Publication History

Abstract

As an increasing number of digital images are generated, a demand for an efficient and effective image retrieval mechanisms grows. In this work, we present a new skeleton-based algorithm for 2D and 3D shape retrieval. The algorithm starts by drawing circles (spheres for 3D) of increasing radius around skeletons. Since each skeleton corresponds to the center of a maximally inscribed circle (sphere), this process results in circles (spheres) that are partially inside the shape. Computing the ratio between pixels that lie within the shape and the total number of pixels allows us to distinguish shapes with similar skeletons. Experimental evaluation of the proposed approach including a comprehensive comparison with the previous techniques demonstrates both effectiveness and robustness of our algorithm for shape retrieval using several 2D and 3D datasets.

References

[1]

Akgul CB, Sankur B, Yemez Y, Schmitt F (2009) 3d model retrieval using probability density-based shape descriptors. IEEE Trans Pattern Anal Mach Intell 31 (6):1117---1133

Digital Library

[2]

Akimaliev M, Demirci MF (2015) Improving skeletal shape abstraction using multiple optimal solutions. Pattern Recogn 48(11):3504---3515

Digital Library

[3]

Andaló FA, Miranda PAV, Torres RDS, Falcão AX (2010) Shape feature extraction and description based on tensor scale. Pattern Recogn 43(1):26---36

Digital Library

[4]

Ankerst M, Kastenmüller G, Kriegel H-P, Seidl T (1999) 3d shape histograms for similarity search and classification in spatial databases. In: Advances in spatial databases. Springer, pp 207---226

Digital Library

[5]

Arbter K, Snyder WE, Burhardt H, Hirzinger G (1990) Application of affine-invariant fourier descriptors to recognition of 3-d objects. IEEE Trans Pattern Anal Mach Intell 12(7):640---647

Digital Library

[6]

Axenopoulos A, Litos G, Daras P (2011) 3d model retrieval using accurate pose estimation and view-based similarity. In: Proceedings of the 1st ACM international conference on multimedia retrieval. ACM, p 41

Digital Library

[7]

Belongie Serge, Malik Jitendra, Puzicha Jan (2002) Shape matching and object recognition using shape contexts. IEEE Trans Pattern Anal Mach Intell 24 (4):509---522

Digital Library

[8]

Ben-Chen M, Gotsman C (2008) Characterizing shape using conformal factors. In: 3DOR, pp 1---8

Digital Library

[9]

Bronstein AM, Bronstein MM, Bruckstein AM, Kimmel R (2008) Analysis of two-dimensional non-rigid shapes. Int J Comput Vis 78(1):67---88

Digital Library

[10]

Bustos B, Schreck T, Walter M, Barrios JM, Schaefer M, Keim D (2012) Improving 3d similarity search by enhancing and combining 3d descriptors. Multimed Tools Appl 58(1):81---108

Digital Library

[11]

Chang X, Yang Y, Hauptmann AG, Xing EP, Yu Y-L (2015) Semantic concept discovery for large-scale zero-shot event detection. In: Proceedings of IJCAI

Digital Library

[12]

Chang X, Yang Y, Xing E, Yu Y (2015) Complex event detection using semantic saliency and nearly-isotonic svm. In: Proceedings of the 32nd international conference on machine learning (ICML-15), pp 1348---1357

Digital Library

[13]

Chang X, Yu Y-L, Yang Y, Hauptmann AG (2015) Searching persuasively: Joint event detection and evidence recounting with limited supervision. In: Proceedings of the 23rd Annual ACM Conference on Multimedia Conference. ACM, pp 581---590

Digital Library

[14]

Chellappa R, Bagdazian R (1984) Fourier coding of image boundaries. IEEE Trans Pattern Anal Mach Intell 6(1):102---105

Digital Library

[15]

Chen D-Y, Tian X-P, Shen Y-T, Ouhyoung M (2003) On visual similarity based 3d model retrieval. In: Computer graphics forum, vol 22. Wiley online library, pp 223---232

[16]

Cohen S, Guibas L (1999) The earth mover's distance under transformation sets. In: Computer vision, 1999. The proceedings of the seventh IEEE international conference on, vol 2. IEEE, pp 1076---1083

Digital Library

[17]

Cornea ND, Demirci MF, Silver D, Shokoufandeh A, Dickinson SJ, Kantor PB (2005) 3d object retrieval using many-to-many matching of curve skeletons. In: Shape Modeling and Applications, 2005 International Conference. IEEE, pp 366---371

Digital Library

[18]

Daliri MR, Torre V (2008) Robust symbolic representation for shape recognition and retrieval. Pattern Recogn 41(5):1782---1798

Digital Library

[19]

Demirci MF, Shokoufandeh A, Keselman Y, Dickinson S, Bretzner L (2003) Many-to-many matching of scale-space feature hierarchies using metric embedding. In: Griffin LD, Lillholm M (eds) Scale Space Methods in Computer Vision, volume 2695 of Lecture Notes in Computer Science. Springer, Berlin Heidelberg, pp 17---32

Digital Library

[20]

Demirci MF, Platel B, Shokoufandeh A, Florack L, Dickinson S (2009) The representation and matching of images using top points. J Math Imaging Vis 35 (2):103---116

Digital Library

[21]

Demirci MF, Osmanlioglu Y, Shokoufandeh A, Dickinson S (2011) Efficient many-to-many feature matching under the ℓ1 norm. Comput Vis Image Underst 115(7):976---983

Digital Library

[22]

Donoser M, Bischof H (2013) Diffusion processes for retrieval revisited. In: 2013 IEEE conference on Computer vision and pattern recognition (CVPR). IEEE, pp 1320---1327

Digital Library

[23]

Eberly D (1994) A differential geometric approach to anisotropic diffusion. In: Bart M, Romeny TH (eds) Geometry-Driven Diffusion in Computer Vision, volume 1 of Computational Imaging and Vision. Springer, Netherlands, pp 371---392

[24]

Ebrahim Y, Ahmed M, Abdelsalam W, Chau S-C (2009) Shape representation and description using the hilbert curve. Pattern Recogn Lett 30(4):348---358

Digital Library

[25]

Eitz M, Richter R, Boubekeur T, Hildebrand K, Alexa M (2012) Sketch-based shape retrieval. ACM Trans Graph 31(4):31

Digital Library

[26]

Frejlichowski D (2011) A three-dimensional shape description algorithm based on polar-fourier transform for 3d model retrieval. In: Heyden A, Kahl F (eds) Image Analysis, volume 6688 of Lecture Notes in Computer Science. Springer, Berlin Heidelberg, pp 457---466

Digital Library

[27]

Funkhouser T, Min P, Kazhdan M, Chen J, Halderman A, Dobkin D, Jacobs D (2003) A search engine for 3d models. ACM Trans Graph (TOG) 22 (1):83---105

Digital Library

[28]

Furuya T, Ohbuchi R (2009) Dense sampling and fast encoding for 3d model retrieval using bag-of-visual features. In: Proceedings of the ACM international conference on image and video retrieval. ACM, p 26

Digital Library

[29]

Gal R, Shamir A, Cohen-Or D (2007) Pose-oblivious shape signature. IEEE Trans Vis Comput Graph 13(2):261---271

Digital Library

[30]

Gopalan R, Turaga P, Chellappa R (2010) Articulation-invariant representation of non-planar shapes. In: Computer vision---ECCV 2010. Springer, pp 286---299

Digital Library

[31]

Granlund GH (1972) Fourier preprocessing for hand print character recognition. IEEE Trans Comput 21(2):195---201

Digital Library

[32]

Guocheng A, Fengjun Z, Hong'an W, Guozhong D (2010) Shape filling rate for silhouette representation and recognition. In: 2010 20th international conference on Pattern recognition (ICPR). IAPR, pp 507---510

Digital Library

[33]

Hilaga M, Shinagawa Y, Kohmura T, Kunii TL (2001) Topology matching for fully automatic similarity estimation of 3d shapes. In: Proceedings of the 28th annual conference on computer graphics and interactive techniques. ACM, pp 203---212

Digital Library

[34]

Horn BKP (1984) Extended gaussian images. IEEE Proc 72(12):1671---1686

[35]

Hu R-X, Jia W, Zhao Ya, Gui J (2012) Perceptually motivated morphological strategies for shape retrieval. Pattern Recogn 45(9):3222---3230

Digital Library

[36]

Iyer N, Jayanti S, Lou K, Kalyanaraman Y, Ramani K (2005) Three-dimensional shape searching: state-of-the-art review and future trends. Comput Aided Des 37(5):509---530

Digital Library

[37]

Iyer N, Kalyanaraman Y, Lou K, Jayanti S, Ramani K (2003) A reconfigurable 3d engineering shape search system: Part i-shape representation. In: ASME 2003 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, pp 89---98

[38]

Kang SB, Ikeuchi K (1991) Determining 3-d object pose using the complex extended gaussian image. In: IEEE computer society conference on Computer vision and pattern recognition, 1991. Proceedings CVPR'91. IEEE, pp 580---585

[39]

Kauppinen H, Seppänen T, Pietikäinen M (1995) An experimental comparison of autoregressive and fourier-based descriptors in 2d shape classification. IEEE Trans Pattern Anal Mach Intell 17(2):201---207

Digital Library

[40]

Kawamura S, Usui K, Furuya T, Ohbuchi Rx (2012) Local goemetrical feature with spatial context for shape-based 3d model retrieval. In: 3DOR, pp 55---58

Digital Library

[41]

Kazhdan M, Funkhouser T, Rusinkiewicz S (2003) Rotation invariant spherical harmonic representation of 3 d shape descriptors. In: Symposium on geometry processing, vol 6

Digital Library

[42]

Kim H-K, Kim J-D (2000) Region-based shape descriptor invariant to rotation, scale and translation. Sig Proc Image Comm 16(1-2):87---93

[43]

Kuang Z, Li Z, Jiang X, Liu Y, Li H (2015) Retrieval of non-rigid 3d shapes from multiple aspects. Comput Aided Des 58:13---23

Digital Library

[44]

Laiche N, Larabi S, Ladraa F, Khadraoui Ax (2014) Curve norMalization for shape retrieval. Signal Process Image Commun 29(4):556---571

[45]

Leng B, Xiong Z (2011) Modelseek: an effective 3d model retrieval system. Multimed Tools Appl 51(3):935---962

Digital Library

[46]

Li B, Johan H (2013) 3d model retrieval using hybrid features and class information. Multimed Tools Appl 62(3):821---846

Digital Library

[47]

Li P, Wang Q, Zhang L (2013) A novel earth mover's distance methodology for image matching with gaussian mixture models ICCV

Digital Library

[48]

Li S-S, Huang Y-D, Yang J-W (2013) Affine invariant ring fourier descriptors. In: International conference on wavelet analysis and pattern recognition, pp 62---66

[49]

Lian Z, Godil A, Bustos B, Daoudi M, Hermans J, Kawamura S, Kurita Y, Lavoué G, Nguyen HV, Ohbuchi R et al (2013) A comparison of methods for non-rigid 3d shape retrieval. Pattern Recogn 46(1):449---461

Digital Library

[50]

Lian Z, Rosin PL, Sun X (2010) Rectilinearity of 3d meshes. Int J Comput Vis 89(2-3):130---151

Digital Library

[51]

Lin CC, Chellappa R (1987) Classification of partial 2d shapes using fourier descriptors. IEEE Trans Pattern Anal Mach Intell 9(5):686---690

Digital Library

[52]

Ling H, Jacobs DW (2005) Using the inner-distance for classification of articulated shapes. In: IEEE computer society conference on Computer vision and pattern recognition, 2005. CVPR 2005, vol 2. IEEE, pp 719---726

Digital Library

[53]

Ling H, Jacobs DW (2007) Shape classification using the inner-distance. IEEE Trans Pattern Anal Mach Intell 29(2):286---299

Digital Library

[54]

Liu T-L, Geiger D (1999) Approximate tree matching and shape similarity. In: The proceedings of the seventh IEEE international conference on Computer vision, 1999, vol 1. IEEE, pp 456---462

[55]

Lou K, Jayanti S, Iyer N, Kalyanaraman Y, Prabhakar S, Ramani K (2003) A reconfigurable 3d engineering shape search system: Part ii-database indexing, retrieval, and clustering. In: ASME 2003 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, pp 169---178

[56]

Lowe DG (2004) Distinctive image features from scale-invariant keypoints. Int J Comput Vis 60(2):91---110

Digital Library

[57]

Mémoli F, Sapiro G (2005) A theoretical and computational framework for isometry invariant recognition of point cloud data. Found Comput Math 5(3):313---347

Digital Library

[58]

Nanni L, Brahnam S, Lumini Ax (2012) Local phase quantization descriptor for improving shape retrieval/classification. Pattern Recogn Lett 33(16):2254---2260

Digital Library

[59]

Novotni M, Klein R (2004) Shape retrieval using 3d zernike descriptors. Comput Aided Des 36(11):1047---1062

Digital Library

[60]

Ohishi Y, Ohbuchi R (2013) Densely sampled local visual features on 3d mesh for retrieval. In: 2013 14th international workshop on Image analysis for multimedia interactive services (WIAMIS). IEEE, pp 1---4

[61]

Ohkita Y, Ohishi Y, Furuya T, Ohbuchi R (2012) Non-rigid 3d model retrieval using set of local statistical features. In: 2012 IEEE international conference on Multimedia and expo workshops (ICMEW). IEEE, pp 593---598

Digital Library

[62]

Osada R, Funkhouser T, Chazelle B, Dobkin D (2001) Matching 3d models with shape distributions. In: SMI 2001 international conference on Shape modeling and applications. IEEE, pp 154---166

Digital Library

[63]

Osada R, Funkhouser T, Chazelle B, Dobkin D (2002) Shape distributions. ACM Trans Graph (TOG) 21(4):807---832

Digital Library

[64]

Papadakis P, Pratikakis I, Perantonis S, Theoharis T (2007) Efficient 3d shape matching and retrieval using a concrete radialized spherical projection representation. Pattern Recogn 40(9):2437---2452

Digital Library

[65]

Papadakis P, Pratikakis I, Theoharis T, Passalis G, Perantonis S (2008) 3d object retrieval using an efficient and compact hybrid shape descriptor. In: Eurographics workshop on 3d object retrieval

Digital Library

[66]

Papadakis P, Pratikakis I, Theoharis T, Perantonis S (2010) Panorama: A 3d shape descriptor based on panoramic views for unsupervised 3d object retrieval. Int J Comput Vis 89(2-3):177---192

Digital Library

[67]

Pedrosa GV, Batista MA, Barcelos CAZ (2013) Image feature descriptor based on shape salience points. Neurocomputing 120:156---163

[68]

Pele O, Werman M (2009) Fast and robust earth mover's distances. In: ICCV

[69]

Rauber TW, Steiger-Garcao AS (1992) Shape description by unl fourier features-an application to handwritten character recognition. In: 11Th IAPR international conference on pattern recognition, pp 466---469

[70]

Rubner Y, Tomasi C, Guibas LJ (2000) The earth mover's distance as a metric for image retrieval. Int J Comput Vis 40(2):99---121

Digital Library

[71]

Ruggeri MR, Patanè G, Spagnuolo M, Saupe D (2010) Spectral-driven isometry-invariant matching of 3d shapes. Int J Comput Vis 89(2-3):248---265

Digital Library

[72]

Schreck T, Scherer M, Walter M, Bustos B, Yoon SM, Kuijper A (2012) Graph-based combinations of fragment descriptors for improved 3d object retrieval. In: Proceedings of the 3rd multimedia systems conference. ACM, pp 23---28

Digital Library

[73]

Sebastian TB, Klein PN, Kimia BB (2004) Recognition of shapes by editing their shock graphs. IEEE Trans Pattern Anal Mach Intell 26(5):550---571

Digital Library

[74]

Sharvit D, Chan J, Tek H, Kimia B (1998) Symmetry-based indexing of image databases. In: 1998. Proceedings. IEEE workshop on Content-based access of image and video libraries. IEEE, pp 56---62

Digital Library

[75]

Shekar BH, Pilar B (2014) Shape representation and classification through pattern spectrum and local binary pattern---a decision level fusion approach. In: 2014 fifth international conference on Signal and image processing (ICSIP). IEEE, pp 218---224

Digital Library

[76]

Shekar BH, Pilar B, Kittler J (2015) An unification of inner distance shape context and local binary pattern for shape representation and classification. In: Proceedings of the 2nd international conference on perception and machine intelligence. ACM, pp 46---55

Digital Library

[77]

Shen W, Bai X, Hu R, Wang H, Latecki LJ (2011) Skeleton growing and pruning with bending potential ratio. Pattern Recogn 44(2):196---209

Digital Library

[78]

Shen Y-T, Chen D-Y, Tian X-P, Ouhyoung M (2003) 3D model search engine based on lightfield descriptors. In: Eurographics

[79]

Shih J-L, Chen H-Y (2009) A 3d model retrieval approach using the interior and exterior 3d shape information. Multimed Tools Appl 43(1):45---62

Digital Library

[80]

Shih J-L, Lee C-H, Wang JTa (2007) A new 3d model retrieval approach based on the elevation descriptor. Pattern Recogn 40(1):283---295

Digital Library

[81]

Shilane P, Min P, Kazhdan M, Funkhouser T (2004) The princeton shape benchmark. In: Shape modeling applications, 2004. proceedings. IEEE, pp 167---178

Digital Library

[82]

Shu X, Wu X-J (2011) A novel contour descriptor for 2d shape matching and its application to image retrieval. Image Vis Comput 29(4):286---294

Digital Library

[83]

Siddiqi K, Bouix S, Tannenbaum A, Zucker SW (2002) Hamilton-jacobi skeletons. Int J Comput Vis 48(3):215---231

Digital Library

[84]

Siddiqi K, Zhang J, Macrini D, Shokoufandeh A, Bouix S, Dickinson S (2008) Retrieving articulated 3-d models using medial surfaces. Mach Vis Appl 19 (4):261---275

Digital Library

[85]

Sipiran I, Bustos B, Schreck T (2013) Data-aware 3d partitioning for generic shape retrieval. Comput Graph 37(5):460---472

Digital Library

[86]

Sirin Y, Demirci MF (2014) Skeleton filling rate for shape recognition. In: 2014 22nd international conference on Pattern recognition (ICPR). IAPR, pp 4005---4009

Digital Library

[87]

Söderkvist O (2001) Computer vision classification of leaves from swedish trees

[88]

Sun J, Ovsjanikov M, Guibas L (2009) A concise and provably informative multi-scale signature based on heat diffusion. In: Computer graphics forum, vol 28. Wiley online library, pp 1383---1392

Digital Library

[89]

Sundar H, Silver D, Gagvani N, Dickinson S (2003) Skeleton based shape matching and retrieval. In: Shape modeling international, 2003. IEEE, pp 130---139

Digital Library

[90]

Tam GKL, Lau RWH (2007) Deformable model retrieval based on topological and geometric signatures. IEEE Trans Vis Comput Graph 13(3):470---482

Digital Library

[91]

Tangelder JWH, Veltkamp RC (2008) A survey of content based 3d shape retrieval methods. Multimed Tools Appl 39(3):441---471

Digital Library

[92]

Van der Zwan M, Meiburg Y, Telea A (2013) A dense medial descriptor for image analysis. In: VISAPP (1), pp 285---293

[93]

Van Otterloo PJ (1991) A Contour-oriented Approach to Shape Analysis. Prentice Hall International (UK) Ltd., Hertfordshire, UK

Digital Library

[94]

Vranic DV (2005) Desire: a composite 3d-shape descriptor. In: IEEE international conference on Multimedia and expo, 2005. ICME 2005. IEEE, pp 4---pp

[95]

Vranić DV, Saupe D (2004) 3d model retrieval. In: Proc SCCG 2000, pp 3---6

[96]

Wang Fan, Guibas LJ (2012) Supervised earth mover's distance learning and its computer vision applications. In: Computer vision---ECCV 2012. Springer, pp 442---455

Digital Library

[97]

Wang J, Bai X, You X, Liu W, Latecki LJ (2012) Shape matching and classification using height functions. Pattern Recogn Lett 33(2):134---143

Digital Library

[98]

Wu J, Rehg JM (2008) Where am i: Place instance and category recognition using spatial pact. In: 2008. CVPR 2008. IEEE conference on Computer vision and pattern recognition. IEEE, pp 1---8

[99]

Xie J, Heng P-A, Shah M (2008) Shape matching and modeling using skeletal context. Pattern Recogn 41(5):1756---1767

Digital Library

[100]

Xu J, Zhang Z, Tung AK, Yu G (2012) Efficient and effective similarity search over probabilistic data based on earth mover's distance. VLDB J Int J Very Large Data Bases 21(4):535---559

Digital Library

[101]

Zhang D, Lu G (2004) Review of shape representation and description techniques. Pattern Recogn 37(1):1---19

Cited By

Jia QChen XWang YFan XLing HLatecki L(2024)A rotation robust shape transformer for cartoon character recognitionThe Visual Computer: International Journal of Computer Graphics10.1007/s00371-023-03123-240:8(5575-5588)Online publication date: 1-Aug-2024
https://dl.acm.org/doi/10.1007/s00371-023-03123-2
Zrour RAndres ESidibe SLenain RLargeteau-Skapin G(2021)A 2D and 3D discrete bisector function based on annulusPattern Analysis & Applications10.1007/s10044-021-00973-124:3(1135-1148)Online publication date: 1-Aug-2021
https://dl.acm.org/doi/10.1007/s10044-021-00973-1
Hammouda GSellami DHammouda A(2020)Pattern recognition based on compound complex shape-invariant Radon transformThe Visual Computer: International Journal of Computer Graphics10.1007/s00371-018-1604-936:2(279-290)Online publication date: 1-Feb-2020
https://dl.acm.org/doi/10.1007/s00371-018-1604-9
Show More Cited By

2D and 3D shape retrieval using skeleton filling rate
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision problems
  2. Computer graphics

Recommendations

Skeleton Filling Rate for Shape Recognition
ICPR '14: Proceedings of the 2014 22nd International Conference on Pattern Recognition

As an increasing number of digital images are generated, a demand for an efficient and effective image retrieval mechanisms grows. In this work, we present a new skeleton-based shape retrieval algorithm, which starts by drawing circles of increasing ...
Shape recognition by bag of skeleton-associated contour parts

We associate a contour point with an object thickness value.We propose a new descriptor to combine both contour and skeleton information.Our method achieves the state-of-the-arts results on several shape dataset. Contour and skeleton are two ...
A 3D shape descriptor based on spectral analysis of medial axis

The medial axis of a 3D shape is widely known for its ability as a compact and complete shape representation. However, there is still lack of a generative description defined over the medial axis directly which limits its actual application to 3D shape ...

Comments

Information & Contributors

Information

Published In

cover image Multimedia Tools and Applications

Multimedia Tools and Applications Volume 76, Issue 6

March 2017

1495 pages

ISSN:1380-7501

Issue’s Table of Contents

Copyright © Copyright © 2017 Springer Science+Business Media New York.

Publisher

Kluwer Academic Publishers

United States

Publication History

Published: 01 March 2017

Author Tags

Qualifiers

Article

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

4
Total Citations
View Citations
0
Total Downloads

Downloads (Last 12 months)0
Downloads (Last 6 weeks)0

Reflects downloads up to 06 Jan 2025

Other Metrics

View Author Metrics

Citations

Cited By

Jia QChen XWang YFan XLing HLatecki L(2024)A rotation robust shape transformer for cartoon character recognitionThe Visual Computer: International Journal of Computer Graphics10.1007/s00371-023-03123-240:8(5575-5588)Online publication date: 1-Aug-2024
https://dl.acm.org/doi/10.1007/s00371-023-03123-2
Zrour RAndres ESidibe SLenain RLargeteau-Skapin G(2021)A 2D and 3D discrete bisector function based on annulusPattern Analysis & Applications10.1007/s10044-021-00973-124:3(1135-1148)Online publication date: 1-Aug-2021
https://dl.acm.org/doi/10.1007/s10044-021-00973-1
Hammouda GSellami DHammouda A(2020)Pattern recognition based on compound complex shape-invariant Radon transformThe Visual Computer: International Journal of Computer Graphics10.1007/s00371-018-1604-936:2(279-290)Online publication date: 1-Feb-2020
https://dl.acm.org/doi/10.1007/s00371-018-1604-9
Boluk ADemirci M(2019)Object recognition based on critical nodesPattern Analysis & Applications10.1007/s10044-018-00777-w22:1(147-163)Online publication date: 1-Feb-2019
https://dl.acm.org/doi/10.1007/s10044-018-00777-w
Zhou WZhong BYang J(2019)Shape Description and Retrieval in a Fused Scale SpaceNeural Information Processing10.1007/978-3-030-36711-4_7(70-82)Online publication date: 12-Dec-2019
https://dl.acm.org/doi/10.1007/978-3-030-36711-4_7

View Options

View options

Media

Figures

Other

Tables

View Issue’s Table of Contents