Detecting, Representing and Attending to Visual Shape

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.

[1]  John K. Tsotsos,et al.  The Roles of Endstopped and Curvature Tuned Computations in a Hierarchical Representation of 2D Shape , 2012, PloS one.

[2]  Linda B. Smith,et al.  Object name Learning Provides On-the-Job Training for Attention , 2002, Psychological science.

[3]  John K. Tsotsos A Computational Perspective on Visual Attention , 2011 .

[4]  J. Todd,et al.  The visual perception of 3D shape q , 2004 .

[5]  Brian Leung,et al.  Component-based Car Detection in Street Scene Images , 2004 .

[6]  Linda B. Smith,et al.  Shape and the first hundred nouns. , 2004, Child development.

[7]  Antonio Jose Rodríguez-Sánchez Intermediate visual representations for attentive recognition systems , 2010 .

[8]  P. O. Bishop,et al.  End-zone region in receptive fields of hypercomplex and other striate neurons in the cat. , 1979, Journal of neurophysiology.

[9]  Ross M. VanDerKlok,et al.  Shape from sound: Evidence for a shape operator in the lateral occipital cortex , 2011, Neuropsychologia.

[10]  R. Brubaker Models for the perception of speech and visual form: Weiant Wathen-Dunn, ed.: Cambridge, Mass., The M.I.T. Press, I–X, 470 pages , 1968 .

[11]  Hans-Jochen Heinze,et al.  The spatial profile of the focus of attention in visual search: Insights from MEG recordings , 2010, Vision Research.

[12]  Peter Janssen,et al.  Anterior Regions of Monkey Parietal Cortex Process Visual 3D Shape , 2007, Neuron.

[13]  A. Parker,et al.  Spatial properties of neurons in the monkey striate cortex , 1987, Proceedings of the Royal Society of London. Series B. Biological Sciences.

[14]  Yen-Wei Chen,et al.  Image recognition by learned linear subspace of combined bag-of-features and low-level features , 2010, 2010 IEEE International Conference on Image Processing.

[15]  John K. Tsotsos,et al.  Shape Representation and Recognition from Multiscale Curvature , 1997, Comput. Vis. Image Underst..

[16]  G. Orban,et al.  Selectivity for 3D shape that reveals distinct areas within macaque inferior temporal cortex. , 2000, Science.

[17]  Charles E Connor,et al.  Underlying principles of visual shape selectivity in posterior inferotemporal cortex , 2004, Nature Neuroscience.

[18]  Demetri Terzopoulos,et al.  Regularization of Inverse Visual Problems Involving Discontinuities , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[19]  T. Poggio,et al.  Hierarchical models of object recognition in cortex , 1999, Nature Neuroscience.

[20]  S Marcelja,et al.  Mathematical description of the responses of simple cortical cells. , 1980, Journal of the Optical Society of America.

[21]  C. Connor,et al.  Responses to contour features in macaque area V4. , 1999, Journal of neurophysiology.

[22]  John K. Tsotsos,et al.  Recognizing planar curves using curvature-tuned smoothing , 1990, [1990] Proceedings. 10th International Conference on Pattern Recognition.

[23]  P. O. Bishop,et al.  Hypercomplex and simple/complex cell classifications in cat striate cortex. , 1978, Journal of neurophysiology.

[24]  J. Bosch,et al.  Sinusoidal Endothelial Dysfunction Precedes Inflammation and Fibrosis in a Model of NAFLD , 2012, PloS one.

[25]  Pietro Perona,et al.  Object class recognition by unsupervised scale-invariant learning , 2003, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings..

[26]  John E. Hummel,et al.  Two Roles for Attention in Shape Perception: A Structural Description Model of Visual Scrutiny , 1998 .

[27]  P. O. Bishop,et al.  Direction-selective cells in complex family in cat striate cortex. , 1980, Journal of neurophysiology.

[28]  J. Todd Review TRENDS in Cognitive Sciences Vol.8 No.3 March 2004 The visual perception of 3D shape q , 2022 .

[29]  F. Attneave Some informational aspects of visual perception. , 1954, Psychological review.

[30]  R. Vogels,et al.  Contribution of Inferior Temporal and Posterior Parietal Activity to Three-Dimensional Shape Perception , 2010, Current Biology.

[31]  John K. Tsotsos,et al.  Attention and Visual Search , 2007, Int. J. Neural Syst..

[32]  K. Rektorys Variational Methods in Mathematics, Science and Engineering , 1977 .

[33]  Keiji Tanaka,et al.  Representation of Visual Features of Objects in the Inferotemporal Cortex , 1996, Neural Networks.

[34]  R. von der Heydt,et al.  Illusory contours and cortical neuron responses. , 1984, Science.

[35]  Jonathan S. Cant,et al.  Scratching Beneath the Surface: New Insights into the Functional Properties of the Lateral Occipital Area and Parahippocampal Place Area , 2011, The Journal of Neuroscience.

[36]  John K. Tsotsos,et al.  Shape representation and recognition from curvature , 1991, Proceedings. 1991 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[37]  Ali Shokoufandeh,et al.  Shock Graphs and Shape Matching , 1998, International Journal of Computer Vision.

[38]  D. Hubel,et al.  Receptive fields, binocular interaction and functional architecture in the cat's visual cortex , 1962, The Journal of physiology.

[39]  Kunihiko Fukushima,et al.  Neocognitron: A self-organizing neural network model for a mechanism of pattern recognition unaffected by shift in position , 1980, Biological Cybernetics.

[40]  C. Connor,et al.  Population coding of shape in area V4 , 2002, Nature Neuroscience.

[41]  A. Sereno,et al.  Attention and memory-related responses of neurons in the lateral intraparietal area during spatial and shape-delayed match-to-sample tasks. , 2006, Journal of neurophysiology.

[42]  M. Corbetta,et al.  Selective and divided attention during visual discriminations of shape, color, and speed: functional anatomy by positron emission tomography , 1991, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[43]  Linda B. Smith,et al.  The place of perception in children's concepts ☆ , 1993 .

[44]  John K. Tsotsos,et al.  The importance of intermediate representations for the modeling of 2D shape detection: Endstopping and curvature tuned computations , 2011, CVPR 2011.

[45]  P. O. Bishop,et al.  Dimensions and properties of end-zone inhibitory areas in receptive fields of hypercomplex cells in cat striate cortex. , 1979, Journal of neurophysiology.

[46]  Peter Janssen,et al.  Extracting 3D structure from disparity , 2006, Trends in Neurosciences.

[47]  Richard N Aslin,et al.  Statistical learning of new visual feature combinations by infants , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[48]  H. A. Pham,et al.  V4 lesions in macaques affect both single- and multiple-viewpoint shape discriminations , 1998, Visual Neuroscience.

[49]  G. Boynton,et al.  Visual Cortex: The Continuing Puzzle of Area V2 , 2004, Current Biology.

[50]  Thomas B. Moeslund,et al.  Long-Term Occupancy Analysis Using Graph-Based Optimisation in Thermal Imagery , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.

[51]  S. Ullman Visual routines , 1984, Cognition.

[52]  Minami Ito,et al.  Representation of Angles Embedded within Contour Stimuli in Area V2 of Macaque Monkeys , 2004, The Journal of Neuroscience.

[53]  Thomas Serre,et al.  Object recognition with features inspired by visual cortex , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[54]  D. Hubel,et al.  Receptive fields and functional architecture of monkey striate cortex , 1968, The Journal of physiology.

[55]  Harry Blum,et al.  An Associative Machine for Dealing with the Visual Field and Some of Its Biological Implications , 1962 .

[56]  Linda B Smith,et al.  They call it like they see it: spontaneous naming and attention to shape. , 2005, Developmental science.

[57]  Eric T. Carlson,et al.  A neural code for three-dimensional object shape in macaque inferotemporal cortex , 2008, Nature Neuroscience.

[58]  Heida Maria Sigurdardottir,et al.  Shape beyond recognition: How object form biases spatial attention and motion perception , 2012 .

[59]  E. Rolls,et al.  View-invariant representations of familiar objects by neurons in the inferior temporal visual cortex. , 1998, Cerebral cortex.

[60]  G. Orban,et al.  Macaque Inferior Temporal Neurons Are Selective for Three-Dimensional Boundaries and Surfaces , 2001, The Journal of Neuroscience.

[61]  Thomas Serre,et al.  Robust Object Recognition with Cortex-Like Mechanisms , 2007, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[62]  C. Connor,et al.  Shape representation in area V4: position-specific tuning for boundary conformation. , 2001, Journal of neurophysiology.

[63]  J. Koenderink,et al.  Photometric Invariants Related to Solid Shape , 1980 .

[64]  Elizabeth S. Spelke,et al.  Principles of Object Perception , 1990, Cogn. Sci..