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Visual shape representation with geometrically characterized contour partitions

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Abstract

This paper proposes a biologically plausible matching method to recognize general shapes based on contour curvature information. The human visual system recognizes general shapes flexibly in real-world scenes through the ventral pathway. The pathway is typically modeled using artificial neural networks. These network models, however, do not construct a shape representation that satisfies the following required constraints: (1) The original shape should be represented by a group of partitioned contours in order to retrieve the whole shape (global information) from the partial contours (local information). (2) Coarse and fine structures of the original shapes should be individually represented in order for the visual system to respond to shapes as quickly as possible based on the least number of their features, and to discriminate between shapes based on detailed information. (3) The shape recognition realized with an artificial visual system should be invariant to geometric transformation such as expansion, rotation, or shear. In this paper, we propose a visual shape representation with geometrically characterized contour partitions described on multiple spatial scales.

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References

  • Asada H, Brady M (1986) The curvature primal sketch. IEEE Trans Pattern Anal 8(1): 2–14

    Article  CAS  Google Scholar 

  • Attalla E, Siy P (2005) Robust shape similarity retrieval based on contour segmentation polygonal multiresolution and elastic matching. Pattern Recogn 38(12): 2229–2241

    Article  Google Scholar 

  • Belongie S, Malik J, Puzicha J (2002) Shape matching and object recognition using shape contexts. IEEE Trans Pattern Anal 24(4): 509–522

    Article  Google Scholar 

  • Ben-Shahar O, Zucker S (2004) Geometrical computations explain projection patterns of long-range horizontal connections in visual cortex. Neural Comput 16(3): 445–476

    Article  PubMed  Google Scholar 

  • Booth MC, Rolls ET (1998) View-invariant representations of familiar objects by neurons in the inferior temporal visual cortex. Cereb Cortex 8(6): 510–523

    Article  PubMed  CAS  Google Scholar 

  • Brincat SL, Connor CE (2004) Underlying principles of visual shape selectivity in posterior inferotemporal cortex. Nat Neurosci 7(8): 880–886

    Article  PubMed  CAS  Google Scholar 

  • Cui M, Femiani J, Hu J, Wonka P, Razdan a (2009) Curve matching for open 2D curves. Pattern Recogn Lett 30(1): 1–10

    Article  Google Scholar 

  • Daliri MR, Torre V (2009) Classification of silhouettes using contour fragments. Comput Vis Image Underst 113(9): 1017–1025

    Article  Google Scholar 

  • Drucker DM, Aguirre GK (2009) Different spatial scales of shape similarity representation in lateral and ventral LOC. Cereb Cortex 19(10): 2269–2280

    Article  PubMed  Google Scholar 

  • Fukushima K (1980) Neocognitron: a self organizing neural network model for a mechanism of pattern recognition unaffected by shift in position. Biol Cybern 36(4): 193–202

    Article  PubMed  CAS  Google Scholar 

  • Grossberg S (2009) ARTSCENE: a neural system for natural scene classification. J Vis 9: 1–19

    Article  PubMed  Google Scholar 

  • Hubel D, Wiesel T (1962) Receptive fields, binocular interaction and functional architecture in the cat’s visual cortex. J Physiol 160(1): 106

    PubMed  CAS  Google Scholar 

  • Inui T (1988) Properties of human visual memory for block patterns. Biol Cybern 187: 179–187

    Article  Google Scholar 

  • Ito M, Tamura H, Fujita I, Tanaka K (1995) Size and position invariance of neuronal responses in monkey inferotemporal cortex. J Neurophysiol 73(1): 218–226

    PubMed  CAS  Google Scholar 

  • Klymenko V, Weisstein N, Topolski R, Hsieh CH (1989) Spatial and temporal frequency in figure-ground organization. Percept Psychophys 45(5): 395–403

    Article  PubMed  CAS  Google Scholar 

  • Lamdan Y, Wolfson H (1988) Geometric hashing: a general and efficient model-based recognition scheme. In: IEEE Int Conf Comput Vis. IEEE Computer Society Press, Washington, pp 238–249

  • Latecki L, Lakamper R (2000) Shape descriptors for non-rigid shapes with a single closed contour. In: Proc CVPR IEEE, Hilton Head Island, pp 424–429

  • Leventhal aG, Thompson KG, Liu D, Zhou Y, Ault SJ (1995) Concomitant sensitivity to orientation, direction, and color of cells in layers 2, 3, and 4 of monkey striate cortex. J Neurosci 15(3 Pt 1): 1808–1818

    PubMed  CAS  Google Scholar 

  • Lier RV, Leeuwenberg E (1995) Multiple completions primed by occlusion patterns. Perception 24: 727–740

    Article  PubMed  Google Scholar 

  • Mai F, Chang C (2010) Affine-invariant shape matching and recognition under partial occlusion. In: 17th IEEE ICIP, 2010, pp 4605–4608

  • Mokhtarian F (1995) Silhouette-based isolated object recognition through curvature scale space. IEEE Trans Pattern Anal 17(5): 539–544

    Article  Google Scholar 

  • Mokhtarian F (1997) Silhouette-based occluded object recognition through curvature scale space. Mach Vis Appl 10(3): 87–97

    Article  Google Scholar 

  • Mokhtarian F (2002) Shape similarity retrieval under affine transforms. Pattern Recogn 35(1): 31–41

    Article  Google Scholar 

  • Mokhtarian F, Mackworth A (1986) Scale-Based description and recognition of planar curves and two-dimensional shapes. IEEE Trans Pattern Anal Mach Intell 8(1): 34–43

    Article  PubMed  CAS  Google Scholar 

  • Mokhtarian F, Mackworth A (1992) A theory of multiscale, curvature-based shape representation for planar curves. IEEE Trans Pattern Anal Mach Intell 14(8): 789–805

    Article  Google Scholar 

  • Mokhtarian F, Abbasi S, Kittler J (1997) Efficient and robust retrieval by shape content through curvature scale space. Ser Softw Eng Knowl 8: 51–58

    Article  Google Scholar 

  • Näsänen R (1999) Spatial frequency bandwidth used in the recognition of facial images. Vis Res 39(23): 3824–3833

    Article  PubMed  Google Scholar 

  • Pasupathy A, Connor CE (2001) Shape representation in area V4: position-specific tuning for boundary conformation. J Neurophysiol 86(5): 2505–2519

    PubMed  CAS  Google Scholar 

  • Pasupathy A, Connor CE (2002) Population coding of shape in area V4. Nat Neurosci 5(12): 1332–1338

    Article  PubMed  CAS  Google Scholar 

  • Richards W, Dawson B, Whittington D (1986) Encoding contour shape by curvature extrema. J Opt Soc Am A 3(9): 1483–1491

    Article  PubMed  CAS  Google Scholar 

  • Riesenhuber M, Poggio T (1999) Hierarchical models of object recognition in cortex. Nat Neurosci 2(11): 1019–1025

    Article  PubMed  CAS  Google Scholar 

  • Sajda P, Finkel LH (1995) Intermediate-level visual representations and the construction of surface perception. J Cogn Neurosci 7(2): 267–291

    Article  Google Scholar 

  • Sakai K, Inui T (2002) A feature-segmentation model of short-term visual memory. Perception 31(5): 579–589

    Article  PubMed  Google Scholar 

  • Sekuler AB, Palmer SE, Flynn C (1994) Local and global processes in visual completion. Psychol Sci 5(5): 260–267

    Article  Google Scholar 

  • Sincich LC, Horton JC (2005) The circuitry of V1 and V2: integration of color, form, and motion. Annu Rev Neurosci 28: 303–326

    Article  PubMed  CAS  Google Scholar 

  • Sprinzak J, Werman M (1994) Affine point matching. Pattern Recogn Lett 15(4): 337–339

    Article  Google Scholar 

  • Tanaka K (1996) Inferotemporal cortex and object vision. Annu Rev Neurosci 19: 109–139

    Article  PubMed  CAS  Google Scholar 

  • Tanaka JW, Farah MJ (1993) Parts and wholes in face recognition. Q J Exp Psychol A 46(2): 225–245

    Article  PubMed  CAS  Google Scholar 

  • Tarr MJ, Bülthoff HH (1998) Image-based object recognition in man, monkey and machine. Cognition 67(1–2): 1–20

    Article  PubMed  CAS  Google Scholar 

  • Victor JD, Conte MM (2006) Encoding and stability of image statistics in working memory. Vis Res 46(24): 4152–4162

    Article  PubMed  Google Scholar 

  • Williamson JR (1996) Neural network for dynamic binding with graph representation: form, linking, and depth-from-occlusion. Neural Comput 8(6): 1203–1225

    Article  PubMed  CAS  Google Scholar 

  • Yang X, Koknar-Tezel S (2009) Locally constrained diffusion process on locally densified distance spaces with applications to shape retrieval. In: Proc CVPR IEEE, pp 357–364

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Authors and Affiliations

  1. System Platforms Research Laboratories, NEC Corporation, 1753, Shimonumabe, Nakahara-Ku, Kawasaki, Kanagawa, 211-8666, Japan

    Yuma Matsuda & Masatsugu Ogawa

  2. Laboratory for Brainware, Research Institute of Electrical Communication, Tohoku University, 2-1-1, Katahira, Aoba-ku, Sendai, Miyagi, 980-8577, Japan

    Masafumi Yano

Authors
  1. Yuma Matsuda
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  2. Masatsugu Ogawa
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  3. Masafumi Yano
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Correspondence to Yuma Matsuda.

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Matsuda, Y., Ogawa, M. & Yano, M. Visual shape representation with geometrically characterized contour partitions. Biol Cybern 106, 295–305 (2012). https://doi.org/10.1007/s00422-012-0496-4

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  • DOI: https://doi.org/10.1007/s00422-012-0496-4

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