An advantage for smooth compared with angular contours in the speed of processing shape.

Curvature along a contour is important for shape perception, and a special role may be played by points of maxima (extrema) along the contour. Angles are discontinuities in curvature, a special case at one extreme of the curvature continuum. We report 4 studies using abstract shapes and comparing polygons (curvature discontinuities at the vertices) and a smoothed version of polygons (no vertices). Polygons are simpler and are defined by a small set of vertices, whereas smoothed shapes have a continuous curvature change along the contour. Angles have also been discussed as an early signal of threat and danger, and on that basis, one may predict faster responses to polygons. However, curved shapes are more typical of the natural environment in which the visual system has evolved. For a detection task, we found faster responses to smooth shapes, not mediated by complexity (Experiment 1). We then tested 3 orthogonal shape tasks: comparison between shapes (detection of repetition; Experiment 2a), comparison after a rotation (Experiment 2b), and detection of bilateral symmetry (Experiment 3). In all tasks, responses for smoothed stimuli were faster; there was also an interaction with type of response: Trials with smooth shapes were faster when a positive response was produced. Overall, there was evidence that smooth shapes with continuous change in curvature along the contour are processed more efficiently, and they tend to be classified as targets. We discuss this in relation to shape analysis and to the preference for smoothed over angular shapes. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

[1]  C. Redies,et al.  Edge-Orientation Entropy Predicts Preference for Diverse Types of Man-Made Images , 2018, Front. Neurosci..

[2]  A. Kitaoka,et al.  Blindness to Curvature and Blindness to Illusory Curvature , 2018, i-Perception.

[3]  Kohske Takahashi Curvature Blindness Illusion , 2017, i-Perception.

[4]  M. Nadal,et al.  Preference for curved contours across cultures. , 2017, Psychology of Aesthetics, Creativity, and the Arts.

[5]  Johan Wagemans,et al.  High entropy of edge orientations characterizes visual artworks from diverse cultural backgrounds , 2017, Vision Research.

[6]  Marcos Nadal,et al.  Preference for Curvature: A Historical and Conceptual Framework , 2016, Front. Hum. Neurosci..

[7]  Marco Bertamini,et al.  The Curvature Effect , 2016 .

[8]  Josep Call,et al.  Common Visual Preference for Curved Contours in Humans and Great Apes , 2015, PloS one.

[9]  Marco Bertamini,et al.  Comparing Angular and Curved Shapes in Terms of Implicit Associations and Approach/Avoidance Responses , 2015, PloS one.

[10]  Tamara N. Gheorghes,et al.  Do observers like curvature or do they dislike angularity? , 2015, British journal of psychology.

[11]  D. Bates,et al.  Fitting Linear Mixed-Effects Models Using lme4 , 2014, 1406.5823.

[12]  Joachim Denzler,et al.  Statistical image properties of print advertisements, visual artworks and images of architecture , 2013, Front. Psychol..

[13]  Marco Bertamini,et al.  The visual system prioritizes locations near corners of surfaces (not just locations near a corner) , 2013, Attention, perception & psychophysics.

[14]  J. Wagemans,et al.  Processing convexity and concavity along a 2-D contour: figure–ground, structural shape, and attention , 2013, Psychonomic bulletin & review.

[15]  Patrick Garrigan,et al.  The Role of Constant Curvature in 2-D Contour Shape Representations , 2011, Perception.

[16]  Martin Lepage,et al.  Symmetry brings an impression of familiarity but does not improve recognition memory. , 2011, Acta psychologica.

[17]  C. Redies,et al.  Statistical regularities in art: Relations with visual coding and perception , 2010, Vision Research.

[18]  Vasanti Jadva,et al.  Infants’ Preferences for Toys, Colors, and Shapes: Sex Differences and Similarities , 2010, Archives of sexual behavior.

[19]  E. Erdfelder,et al.  Statistical power analyses using G*Power 3.1: Tests for correlation and regression analyses , 2009, Behavior research methods.

[20]  David C. Zhu,et al.  Recognizing Threat: A Simple Geometric Shape Activates Neural Circuitry for Threat Detection , 2009, Journal of Cognitive Neuroscience.

[21]  Johan Wagemans,et al.  Delayed shape matching benefits from simplicity and symmetry , 2009, Vision Research.

[22]  Paul J. Silvia,et al.  Do People Prefer Curved Objects? Angularity, Expertise, and Aesthetic Preference , 2009 .

[23]  Marco Bertamini,et al.  Detection of convexity and concavity in context. , 2008, Journal of experimental psychology. Human perception and performance.

[24]  Jonathan W Peirce,et al.  Selective mechanisms for simple contours revealed by compound adaptation. , 2008, Journal of vision.

[25]  Elena Gheorghiu,et al.  Spatial properties of curvature-encoding mechanisms revealed through the shape-frequency and shape-amplitude after-effects , 2008, Vision Research.

[26]  Manish Singh,et al.  Geometric determinants of shape segmentation: Tests using segment identification , 2007, Vision Research.

[27]  Christine L Larson,et al.  The shape of threat: simple geometric forms evoke rapid and sustained capture of attention. , 2007, Emotion.

[28]  M. Bar,et al.  Visual elements of subjective preference modulate amygdala activation , 2007, Neuropsychologia.

[29]  Jonathan W. Peirce,et al.  PsychoPy—Psychophysics software in Python , 2007, Journal of Neuroscience Methods.

[30]  Elena Gheorghiu,et al.  The spatial feature underlying the shape-frequency and shape-amplitude after-effects , 2007, Vision Research.

[31]  Marco Bertamini,et al.  The Perceived Structural Shape of Thin (wire-like) Objects is Different from That of Silhouettes , 2006, Perception.

[32]  M. Bar,et al.  Humans Prefer Curved Visual Objects , 2006, Psychological science.

[33]  J. Wagemans,et al.  Segmentation of object outlines into parts: A large-scale integrative study , 2006, Cognition.

[34]  Bill Triggs,et al.  Histograms of oriented gradients for human detection , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[35]  Jacob Feldman,et al.  Detection of change in shape: an advantage for concavities , 2003, Cognition.

[36]  Jacob Feldman,et al.  Visual comparisons within and between object parts: evidence for a single-part superiority effect , 2003, Vision Research.

[37]  Marco Bertamini,et al.  The shape of holes , 2003, Cognition.

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

[39]  Alessandro Treves,et al.  Is the world full of circles? , 2002, Journal of vision.

[40]  S. Dakin,et al.  Snakes and ladders: the role of temporal modulation in visual contour integration , 2001, Vision Research.

[41]  Brian A. Nosek,et al.  THE GO/NO-GO ASSOCIATION TASK , 2001 .

[42]  H. Ross,et al.  Information Concentration along the Boundary Contours of Naturally Shaped Solid Objects , 2001, Perception.

[43]  P U Tse,et al.  Curvature discontinuities are cues for rapid shape analysis , 2001, Perception & psychophysics.

[44]  C. Gilbert,et al.  On a common circle: natural scenes and Gestalt rules. , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[45]  P. Cavanagh,et al.  A shape-contrast effect for briefly presented stimuli. , 1998, Journal of experimental psychology. Human perception and performance.

[46]  N. Schwarz,et al.  Effects of Perceptual Fluency on Affective Judgments , 1998 .

[47]  Donald D. Hoffman,et al.  Salience of visual parts , 1997, Cognition.

[48]  M Kubovy,et al.  Detection of symmetry and perceptual organization: the way a lock-and-key process works. , 1997, Acta psychologica.

[49]  Jon Driver,et al.  Obligatory edge-assignment in vision: The role of figure and part segmentation in symmetry detection. , 1995 .

[50]  David J. Field,et al.  Contour integration by the human visual system: Evidence for a local “association field” , 1993, Vision Research.

[51]  Neil A. Macmillan,et al.  Detection Theory: A User's Guide , 1991 .

[52]  Jan J. Koenderink,et al.  Solid shape , 1990 .

[53]  Michael Leyton,et al.  Inferring Causal History from Shape , 1989, Cogn. Sci..

[54]  Donald D. Hoffman,et al.  Parts of recognition , 1984, Cognition.

[55]  G. Logan On the ability to inhibit thought and action , 1984 .

[56]  J J Koenderink,et al.  What Does the Occluding Contour Tell Us about Solid Shape? , 1984, Perception.

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

[58]  L. Palumbo,et al.  The aesthetics of smooth contour curvature in historical context , 2015 .

[59]  S. Palmer,et al.  A century of Gestalt psychology in visual perception: I. Perceptual grouping and figure-ground organization. , 2012, Psychological bulletin.

[60]  J. Wagemans,et al.  Perceptual saliency of points along the contour of everyday objects: A large-scale study , 2008 .

[61]  Geoff G Cole,et al.  Object and spatial representations in the corner enhancement effect. , 2007, Perception & psychophysics.

[62]  J. Feldman,et al.  Information along contours and object boundaries. , 2005, Psychological review.

[63]  Brian A. Nosek,et al.  NOSEK AND BANAJI T HE G O / NO-GO ASSOCIAT ION TASK THE GO / NO-GO ASSOCIATION TASK , 2001 .

[64]  J. Hulleman,et al.  Concavities as basic features in visual search: Evidence from search asymmetries , 2000, Perception & psychophysics.

[65]  Michael Brady,et al.  The Curvature Primal Sketch , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[66]  Michael C. Corballis,et al.  On the perception of symmetrical and repeated patterns , 1974 .