Abstract
The importance of shape detection, representation and recognition is not disputed by any relevant discipline and is an integral part of visual perception by both animals and machines. However, to date, there is no comprehensive theoretical framework of how to deal with visual shape. Here, we present the beginnings of such a framework and attempt to integrate the means to detect, represent and recognize shapes, specifically two-dimensional silhouettes. Of note is the inclusion of an attentional scheme primarily because there is growing evidence that human perception involves such a capacity yet how this might occur is virtually unexamined. Secondarily, the ability to attend to shape and shape elements is central to our ability to not only recognize shapes and objects, but also to reason about shape, solve problems involving shape, manipulate shapes and perform spatial reasoning.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Attneave F (1954) Some informational aspects of visual perception. Psychol Rev 61:183–193
Bishop P, Kato H, Orban G (1980) Direction selective cells in complex family in cat striate cortex. J Neurophysiol 43:1266–1283
Blum H (1962) An associative machine for dealing with the visual field and some of its biological implications. Air Force Cambridge Research Labs, L G Hanscom Field, Mass, Feb 1962
Blum H (1967) A transformation for extracting descriptors of shape. In: Wathen-Dunn W (ed) Models for the perception of speech and visual forms. MIT Press, Cambridge, pp 362–380
Booth M, Rolls E (1998) View-invariant representations of familiar objects by neurons in the inferior temporal visual cortex. Cereb Cortex 8(6):510–523
Boynton G, Hegde J (2004) Visual cortex: the continuing puzzle of area v2. Curr Biol 14(13):R523–R524
Brincat S, Connor C (2004) Underlying principles of visual shape selectivity in posterior inferotemporal cortex. Nat Neurosci 7(8):880–886
Cant JS, Goodale MA (2011) Scratching beneath the surface: new insights into the functional properties of the lateral occipital area and parahippocampal place area. J Neurosci 31(22):8248–8258
Clements DH, Sarama J (2000) What do Children Know about Shapes? In: Teaching children mathematics. April 2000, The National Council of Teachers of Mathematics, Inc, pp 482–488
Corbetta M, Miezin F, Dobmeyer S, Shulman GL, Petersen SE (1991) Selective and divided attention during visual discriminations of shape, color, and speed: functional anatomy by positron emission tomography. J Neurosci 11(9):2393–2402
Dobbins A (1992) Difference models of visual cortical Neurons. Doctoral dissertation, Department of Electrical Engineering, McGill University
Dudek G, Tsotsos JK (1997) Shape representation and recognition from multiscale curvature. Comput Vis Image Underst 68(2):170–189
Dudek G, Tsotsos JK (1991) Shape representation and recognition from curvature. In: Proc computer vision and pattern recognition, pp 35–41
Dudek G, Tsotsos JK (1990) Recognizing planar curves using curvature-tuned smoothing. In: Proceedings 10th international conference on pattern recognition, vol 1, pp 130–135
Durand JB, Nelissen K, Joly O, Wardak C, Todd J, Norman F, Janssen P, Vanduffel W, Orban G (2007) Anterior regions of monkey parietal cortex process visual 3D shape. Neuron 55:493–505
Fergus R, Perona P, Zisserman A (2003) Object class recognition by unsupervised scale-invariant learning. In: CVPR, vol 2, p 264
Fiser J, Aslin RN (2002) Statistical learning of new visual feature combinations by infants. Proc Natl Acad Sci USA 99:15822–15826
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
Gershfokk-Stowe L, Smith LB (2004) Shape and the first hundred nouns. Child Dev 75(4):1098–1114
Han X, Chen Y, Ruan X (2010) Image recognition by learned linear subspace of combined bag-of-features and low-level features. In: ICIP
Hawken M, Parker A (1987) Spatial properties of neurons in the monkey striate cortex. Proc R Soc Lond B, Biol Sci 231:251–288
Hopf J-M, Boehler CN, Schoenfeld MA, Heinze H-J, Tsotsos JK (2010) The spatial profile of the focus of attention in visual search: insights from MEG recordings. Vis Res 50(14):1312–1320
Hubel D, Wiesel T (1962) Receptive fields, binocular interaction and functional architecture in the cat’s visual cortex. J Physiol 160:106–154
Hubel D, Wiesel T (1968) Receptive fields and functional architecture of monkey striate cortex. J Physiol 195(1):215–243
Hummel JE, Stankiewicz BJ (1998) Two roles for attention in shape perception: a structural description model of visual scrutiny. Vis Cogn 5:49–79
Ito M, Komatsu H (2004) Representation of angles embedded within contour stimuli in area v2 of macaque monkeys. J Neurosci 24(13):3313–3324
James TW, Stevenson RA, Kim S, VanDerKlok RM, James KH (2011) Shape from sound: evidence for a shape operator in the lateral occipital cortex. Neuropsychologia 49:1807–1815
Janssen P, Vogels R, Orban G (2000) Selectivity for 3D shape that reveals distinct areas within macaque inferior temporal cortex. Science 288:2054–2056
Janssen P, Vogels R, Liu Y, Orban G (2001) Macaque inferior temporal neurons are selective for three-dimensional boundaries and surfaces. J Neurosci 21:9419–9429
Jones SS, Smith LB (1993) The place of perception in children’s concepts. Cogn Dev 8:113–139
Kato H, Bishop P, Orban G (1978) Hypercomplex and simple/complex cells classifications in cat striate cortex. J Neurophysiol 41:1071–1095
Koenderink JJ, van Doorn AJ (1980) Photomettric invariants related to solid shape. Opt Acta 27(7):981–996
Kruijne W, Tsotsos JK (2011) Visuo-cognitive routines: reinterpreting the theory of visual routines as a framework for visual cognition. Technical Report CSE-2011-05, Dept of Computer Science & Engineering, York University
Leung B (2004) Component-based car detection in street scene IMages. PhD thesis, Massachusetts Institute of Technology, Dept of Electrical Engineering and Computer Science
Marcelja S (1980) Mathematical description of the responses of simple cortical cells. J Opt Soc Am 70(11):1297–1300
Merigan W, Pham H (1998) 4 lesions in macaques affect both single and multiple-viewpoint shape discriminations. Vis Neurosci 15:359–367
Orban G, Kato H, Bishop P (1979) Dimensions and properties of end-zone inhibitory areas of hypercomplex cells in cat striate cortex. J Neurophysiol 42:833–849
Orban G, Kato H, Bishop P (1979) End-zone region in receptive fields of hypercomplex and other striate neurons in the cat. J Neurophysiol 42:818–832
Orban G, Janssen P, Vogels R (2006) Extracting 3D structure from disparity. Trends Neurosci 29:466–473
Pasupathy A, Connor C (1999) Responses to contour features in macaque area V4. J Neurophysiol 82(5):2490–2502
Pasupathy A, Connor C (2001) Shape representation in area V4: position-specific tuning for boundary conformation. J Neurophysiol 86(5):2505–2519
Pasupathy A, Connor C (2002) Population coding of shape in area V4. Nat Neurosci 5(12):1332–1338
Rektorys K (1980) Variational methods in mathematics, science and engineering. Reidel, Dordrecht
Riesenhuber M, Poggio T (1999) Hierarchical models of object recognition in cortex. Nat Neurosci 2(11):1019–1025
RodrÃguez-Sánchez AJ, Simine E, Tsotsos JK (2007) Attention and visual search. Int J Neural Syst 17(4):275–288
RodrÃguez-Sánchez A (2010) Intermediate visual representations for attentive recognition systems. PhD, York University
Rodriguez-Sanchez A, Tsotsos JK (2011) The importance of intermediate representations for the modeling of 2D shape detection: endstopping and curvature tuned computations. In: Proc IEEE computer vision and pattern recognition, Colorado Springs, CO
RodrÃguez-Sánchez A, Tsotsos J (2012) The roles of endstopped and curvature tuned computations in a hierarchical representation of 2D shape. PLoS ONE 7(8):1–13
Samuelson LK, Smith LB (2005) They call it like they see it: spontaneous naming and attention to shape. Dev Sci 8(2):182–198
Sereno AB, Amador SC (2006) Attention and memory-related responses of neurons in the lateral intraparietal area during spatial and shape-delayed match-to-sample tasks. J Neurophysiol 95:1078–1098
Serre T, Wolf L, Bileschi S, Riesenhuber M (2007) Robust object recognition with cortex-like mechanisms. IEEE Trans Pattern Anal Mach Intell 29(3):411–426
Serre T, Wolf L, Poggio T (2005) Object recognition with features inspired by visual cortex. In: IEEE conference on computer vision and pattern recognition
Siddiqi K, Shokoufandeh A, Dickinson SJ, Zucker SW (1999) Shock graphs and shape matching. Int J Comput Vis 35(1):13–32
Sigurdardottir HM, Michalak SM, Sheinberg DL (2012) Shape beyond recognition: how object form biases spatial attention and motion perception. J Vis 12(9):665
Smith LB, Jones SS, Landau B, Gershkoff-Stowe L, Samuelson L (2002) Object name learning provides on-the-job training for attention. Psychol Sci 13(1):13–19
Spelke E (2000) Principles of object perception. Cogn Sci 14:29–56
Tanaka K (1996) Representation of visual features of objects in the inferotemporal cortex. Neural Netw 9(8):1459–1475
Terzopoulos D (1986) Regularization of inverse visual problems involving discontinuities. IEEE Trans Pattern Anal Mach Intell 8(4):413–424
Todd JT (2004) The visual perception of 3D shape. Trends Cogn Sci 8(3):115–121
Tsotsos JK (2011) A computational perspective on visual attention. MIT Press, Cambridge
Ullman S (1984) Visual routines. Cognition 18(1–3):97–159
Verhoef BE, Vogels R, Janssen P (2010) Contribution of inferior temporal and posterior parietal activity to three-dimensional shape perception. Curr Biol 20(10):909–913
von der Heydt R, Peterhans E, Baumgartner G (1984) Illusory contours and cortical neuron responses. Science 224(4654):1260–1262
Yamane Y, Carlson E, Bowman K, Wang Z, Connor C (2008) A neural code for three-dimensional object shape in macaque inferotemporal cortex. Nat Neurosci 11:1352–1360
Acknowledgements
This research was funded by the Natural Sciences and Engineering Research Council of Canada and Canada Research Chairs Program.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag London
About this chapter
Cite this chapter
RodrÃguez-Sánchez, A.J., Dudek, G.L., Tsotsos, J.K. (2013). Detecting, Representing and Attending to Visual Shape. In: Dickinson, S., Pizlo, Z. (eds) Shape Perception in Human and Computer Vision. Advances in Computer Vision and Pattern Recognition. Springer, London. https://doi.org/10.1007/978-1-4471-5195-1_29
Download citation
DOI: https://doi.org/10.1007/978-1-4471-5195-1_29
Publisher Name: Springer, London
Print ISBN: 978-1-4471-5194-4
Online ISBN: 978-1-4471-5195-1
eBook Packages: Computer ScienceComputer Science (R0)