The Influence of Painting Composition on Human Perception

in Seeing and Perceiving
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Artists have long explored the way in which we see the world, and they have developed their own tools to portray their vision. The present study investigated whether the compositional information in paintings, an artistic device invented by artists, is utilized when people view paintings. In Experiment 1, we categorized paintings depending on their compositions through experts’ ratings. Using the stimuli from Experiment 1, Experiment 2 tested if the compositional information interferes with a target detection task. We found that the false alarms increased when the targets and distracters had the same composition compared to when they were different. Finally, Experiments 3A and 3B examined whether composition information influences the perceptual similarity of paintings. Through a multi-dimensional scaling analysis, we first showed that paintings with the same composition were proximately located in the mental space (Experiment 3A). Using this distance from the MDS analysis, we found that performance on the target detection task decreased as this distance became close (Experiment 3B). These results suggest that people make use of compositions in paintings, thus providing a possible link between artworks and the human visual system.

The Influence of Painting Composition on Human Perception

in Seeing and Perceiving

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References

ArnheimR. (2004). Visual Thinking: Thirty-Fifth Anniversary Printing. University of California PressUSA.

BrainardD. H. (1997). The psychophysics toolboxSpatial Vision 10433436.

CavanaghP. (2005). The artist as neuroscientistNature 434301307.

ChunM. M. (2000). Contextual cueing of visual attentionTrends Cognit. Sci. 4170178.

ChunM. M.JiangY. V. (1998). Contextual cueing: implicit learning and memory of visual context guides spatial attentionCognit. Psychol. 362871.

ChunM. M.JiangY. V. (1999). Top-down attentional guidance based on implicit learning of visual covariationPsycholog. Sci. 10360365.

ChunM. M.PotterM. C. (1995). A two-stage model for multiple target detection in rapid serial visual presentationJ. Exper. Psychol. Human Percept. Perform. 21109127.

ConwayB. R.LivingstoneM. S. (2007). Perspectives on science and artCurr. Opinion Neurobiol. 17476482.

De ValoisR. L.De ValoisK. K. (1990). Spatial Vision. Oxford University Press.

DuncanJ.HumphreysG. W. (1989). Visual search and stimulus similarityPsycholog. Rev. 96433458.

EpsteinR.KanwisherN. G. (1998). A cortical representation of the local visual environmentNature 392598601.

EvansK. K.TreismanA. (2005). Perception of objects in natural scenes: is it really attention free?J. Exper. Psychol. Human Percept. Perform. 3114761492.

GoffauxV.RossionB. (2006). Faces are ‘spatial’ — holistic face perception is supported by low spatial frequenciesJ. Exper. Psychol. Human Percept. Perform. 3210231039.

GrahamD. J.FieldD. J. (2007). Statistical regularities of art images and natural scenes: spectra, sparseness and nonlinearitiesSpatial Vision 21149164.

GrahamD. J.MengM. (2011). Artistic representations: clues to efficient coding in human visionVisual Neurosci. 28371379.

GrahamD. J.RediesC. (2010). Statistical regularities in art: relations with visual coding and perceptionVision Research 5015031509.

GrahamD. J.FriedenbergJ.RockmoreD.FieldD. J. (2010). Mapping the similarity space of paintings: image statistics and visual perceptionVisual Cognit. 18559573.

GreeneM. R.OlivaA. (2009a). Recognition of natural scenes from global properties: seeing the forest without representing the treesCognit. Psychol. 58137176.

GreeneM. R.OlivaA. (2009b). The briefest of glances: the time course of natural scene understandingPsycholog. Sci. 20464472.

JiangY. V.WagnerL. C. (2004). What is learned in spatial contextual cuing — configuration or individual locations?Percept. Psychophys. 66454463.

KimC.-Y.BlakeR. (2007). Brain activity accompanying perception of implied motion in abstract paintingsSpatial Vision 20545560.

KonkleT.BradyT. F.AlvarezG. A.OlivaA. (2010). Scene memory is more detailed than you think: the role of categories in visual long-term memoryPsycholog. Sci. 2115511556.

LivingstoneM. S. (2002). Vision and Art: The Biology of Seeing. Harry N. Abrams PublishersNew York, USA.

NosofskyR. M. (1987). Attention and learning processes in the identification and categorization of integral stimuliJ. Exper. Psychol. Learn. Mem. Cognit. 1387108.

PeliE. (1990). Contrast in complex imagesJ. Optic. Soc. Amer. A 720322040.

PelliD. G. (1997). The VideoToolbox software for visual psychophysics: transforming numbers into moviesSpatial Vision 10437442.

PooreH. R. (1903). Pictorial Composition and the Critical Judgment of Pictures. G. P. Putnam’s SonsNew York, USA.

RaymondJ. E.ShapiroK. L.ArnellK. M. (1992). Temporary suppression of visual processing in an RSVP task: an attentional blink?J. Exper. Psychol. Human Percept. Perform. 18849860.

RaymondJ. E.ShapiroK. L.ArnellK. M. (1995). Similarity determines the attentional blinkJ. Exper. Psychol. Human Percept. Perform. 21653662.

SanockiT. (2003). Representation and perception of scenic layoutCognit. Psychol. 474386.

SanockiT.EpsteinW. (1997). Priming spatial layout of scenesPsycholog. Sci. 8374378.

SchynsP. G.OlivaA. (1994). From blobs to boundary edges: Evidence for time- and spatial-scale-dependent scene recognitionPsycholog. Sci. 5195200.

ShepardR. N. (1962a). The analysis of proximities: multidimensional scaling with an unknown distance function, IPsychometrika 27125140.

ShepardR. N. (1962b). The analysis of proximities: multidimensional scaling with an unknown distance function, IIPsychometrika 27219246.

TylerC. W. (1998). Painters centre one eye in portraitsNature 392877878.

TylerC. W. (2007). Some principles of spatial organization in artSpatial Vision 20509530.

WardR.DuncanJ.ShapiroK. L. (1997). Effects of similarity, difficulty, and nontarget presentation on the time course of visual attentionPercept. Psychophys. 59593600.

WölfflinH. (1950). Principles of Art History. Dover PublicationsNew York, USA.

ZekiS.LambM. (1994). The neurology of kinetic artBrain 117607636.

Figures

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    Proportions (%) of fitness rating scores of how close the paintings are to the typical compositions.

  • View in gallery

    The procedure of Experiment 2: each trial was initiated with a black fixation cross when the participants pressed the space bar. A cue screen which indicated the target proceeded for 1000 ms followed by a black fixation cross for 1000 ms. Then, an RSVP sequence of 6 images was presented for 450 ms (75 ms each). A blue fixation cross appeared at the end for the participants to report whether or not they detected (via the ‘1’ key for yes or the ‘2’ key for no) the target within the RSVP stream.

  • View in gallery

    The hit (a) and false alarm rates (b) obtained from Experiment 2. Error bars denote the standard errors of the mean.

  • View in gallery

    The procedure of Experiment 3: (a) examples of the timelines of the learning phase. A trial began with a fixation cross after a click of the wheel button on the mouse by the participant. Then, an image and a number appeared on the screen simultaneously for 1000 ms for the participants to memorize. (b) Examples of the timelines of the testing phase. A trial was initiated in the same way as the learning phase. A cue screen was presented for 75 ms followed by a fixation cross for 1000 ms. Then, a number pad was shown for the participants to click on the numbers that they had learned during the cue image.

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    The results of Experiment 3A: (a) the result obtained by the MDS analysis. Two paintings with the same composition contributed to one point. (b) Mean distances among within-composition data points for defined (HOR-L, PYR-L, VER-P and PYR-P) and non-defined (NEU-L and NEU-P) compositions in the mental space.

  • View in gallery

    The hit (a) and false alarm rates (b) obtained from Experiment 3B. Error bars denote the standard error of the mean.

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