Color coding in the cortex: a modified approach to bottom-upvisual attention
Itti and Koch’s (Vision Research 40:1489–1506,2000) saliency-based visual attention model is a broadlyaccepted model that describes how attention processes aredeployed in the visual cortex in a pure bottom-up strategy.This work complements their model by modifying the colorfeature calculation. Evide...
- Autores:
-
Ramírez Moreno, David Fernando
Ramírez Villegas, Juan Felipe
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2012
- Institución:
- Universidad Autónoma de Occidente
- Repositorio:
- RED: Repositorio Educativo Digital UAO
- Idioma:
- eng
- OAI Identifier:
- oai:red.uao.edu.co:10614/11620
- Acceso en línea:
- http://red.uao.edu.co//handle/10614/11620
https://doi.org/10.1007/s00422-012-0522-6
- Palabra clave:
- Color Perception
Models, Theoretical
Visual Cortex
Humans
Percepción de Color
Corteza Visual
Saliency
Visual attention
Double-opponentcell
Center-surround difference
Color map
- Rights
- openAccess
- License
- Derechos Reservados - Universidad Autónoma de Occidente
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Color coding in the cortex: a modified approach to bottom-upvisual attention |
| title |
Color coding in the cortex: a modified approach to bottom-upvisual attention |
| spellingShingle |
Color coding in the cortex: a modified approach to bottom-upvisual attention Color Perception Models, Theoretical Visual Cortex Humans Percepción de Color Corteza Visual Saliency Visual attention Double-opponentcell Center-surround difference Color map |
| title_short |
Color coding in the cortex: a modified approach to bottom-upvisual attention |
| title_full |
Color coding in the cortex: a modified approach to bottom-upvisual attention |
| title_fullStr |
Color coding in the cortex: a modified approach to bottom-upvisual attention |
| title_full_unstemmed |
Color coding in the cortex: a modified approach to bottom-upvisual attention |
| title_sort |
Color coding in the cortex: a modified approach to bottom-upvisual attention |
| dc.creator.fl_str_mv |
Ramírez Moreno, David Fernando Ramírez Villegas, Juan Felipe |
| dc.contributor.author.none.fl_str_mv |
Ramírez Moreno, David Fernando Ramírez Villegas, Juan Felipe |
| dc.subject.mesh.eng.fl_str_mv |
Color Perception Models, Theoretical Visual Cortex |
| topic |
Color Perception Models, Theoretical Visual Cortex Humans Percepción de Color Corteza Visual Saliency Visual attention Double-opponentcell Center-surround difference Color map |
| dc.subject.mesh.spa.fl_str_mv |
Humans |
| dc.subject.decs.spa.fl_str_mv |
Percepción de Color Corteza Visual |
| dc.subject.proposal.eng.fl_str_mv |
Saliency Visual attention Double-opponentcell Center-surround difference Color map |
| description |
Itti and Koch’s (Vision Research 40:1489–1506,2000) saliency-based visual attention model is a broadlyaccepted model that describes how attention processes aredeployed in the visual cortex in a pure bottom-up strategy.This work complements their model by modifying the colorfeature calculation. Evidence suggests that S-cone responsesare elicited in the same spatial distribution and have the samesign as responses to M-cone stimuli; these cells are tenta-tively referred to as red-cyan. For other cells, the S-coneinput seems to be aligned with the L-cone input; these cellsmight be green-magenta cells. To model red-cyan and green-magenta double-opponent cells, we implement a center-sur-round difference approach of the aforementioned model. Theresulting color maps elicited enhanced responses to colorsalient stimuli when compared to the classic ones at highstatistical significance levels. We also show that the modi-fied model improves the prediction of locations attended byhuman viewers |
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2012 |
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2012-09 |
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2019-11-29T15:43:43Z |
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2019-11-29T15:43:43Z |
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Artículo de revista |
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Ramirez-Villegas, J.F., Ramirez-Moreno, D.F. Color coding in the cortex: a modified approach to bottom-up visual attention. Biol Cybern 107, 39–47 (2013). https://doi.org/10.1007/s00422-012-0522-6 |
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http://red.uao.edu.co//handle/10614/11620 |
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https://doi.org/10.1007/s00422-012-0522-6 |
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Ramirez-Villegas, J.F., Ramirez-Moreno, D.F. Color coding in the cortex: a modified approach to bottom-up visual attention. Biol Cybern 107, 39–47 (2013). https://doi.org/10.1007/s00422-012-0522-6 |
| url |
http://red.uao.edu.co//handle/10614/11620 https://doi.org/10.1007/s00422-012-0522-6 |
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eng |
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eng |
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Biological Cybernetics. Volumen 107, número 1 (September 2012); páginas 39-47 |
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47 |
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39 |
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107 |
| dc.relation.ispartofjournal.eng.fl_str_mv |
Biological Cybernetics |
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Bergen JR, Julesz B (1983) Parallel versus serial processing in rapid pattern discrimination. Nature 303:696–698 Bollman M, Hoischen R, Mertsching B (1997) In: Berlin et al (eds) Integration of static and dynamic scene features guiding visual attention. Springer, pp 483–490 Burt PJ, Adelson EH (1983) The Laplacian pyramid as a compact image code. IEEE Trans Commun 31:532–540 Conway BR (2001) Spatial structure of cone inputs to color cells in alert macaque primary visual cortex (V-1). J Neurosci 21:2768–2783 Conway BR (2009) Color vision, cones and color-coding in the cortex. Neuroscientist 15:274–290 Conway BR, Livingstone MS (2006) Spatial and temporal properties of cone signals in alert macaque primary visual cortex. J Neurosci 26:10826–10846 Conway BR, Hubel DH, Livingstone MS (2002) Color contrast in macaque V1. Cereb Cortex 12:915–925 De Brecht M, Saiki J (2006) A neural network implementation of a saliency map model. Neural Netw 19:1467–1474 Desimone R, Duncan J (1995) Neural mechanisms of selective visual attention. Annu Rev Neurosci 18:193–222 Engel S, Zhang X,Wandell B (1997) Colour tuning in human visual cortex measured with functional magnetic resonance imaging. Nature 388:68–71 Fawcett T (2006) An introduction to ROC analysis. Pat Rec Lett 27:861–874 Gao D, Vasconcelos N (2007) Bottom-up saliency is a discriminant process. Proceedings of the IEEE international conference on computer visión Gegenfurtner KR, Kiper DC (2003) Color vision. Annu Rev Neurosci 26:181–206 Hofer H, Singer B, Williams DR (2005) Different sensations from cones with the same photopigment. J Vis 5:444–454 Itti L (2000) Models of bottom-up and top-down visual attention. Dissertation, California Institute of Technology, Pasadena, CA Itti L (2004) Automatic foveation for video compression using a neurobiological model of visual attention. IEEE Trans Image Process 13:1304–1318 Itti L, Koch C (2000) A saliency-based search mechanism for overt and covert shifts of visual attention. Vis Res 40:1489–1506 Itti L, Koch C (2001) Computational modeling of visual attention. Nat Rev Neurosci 2:194–203 Itti L, Koch C, Niebur E (1998) A model of saliency-based visual attention for rapid scene analysis. IEEE Trans Patt Anal Mach Intel 20:1254–1259 Johnson EN, Hawken MJ, Shapley R (2001) The spatial transformation of color in the primary visual cortex of the macaque monkey. Nat Neurosci 4:409–416 Koch C, Ullman S (1985) Shifts in selective visual attention: towards the underlying neural circuitry. Hum Neurobiol 4:219–227 Liu T, Sun J, Zheng NN, Tang X, Shum HY (2007a) Learning to detect a salient object. Proceedings of IEEE computer society conference on computer and vision pattern recognition Liu T, Sun J, Zheng NN, Tang X, Shum HY (2007b) MSRA Salient Object Database. Microsoft Research. http://research.microsoft.com/en-us/um/people/jiansun/salientobject/salient_object.htm. Accessed 12 June 2012 Masciocchi CM, Mihalas S, Parkhurst D, Niebur E (2009) Everyone knows what is interesting: salient locations which should be fixated. J Vis 9:1–22 Peters RJ, Iyer A, Itti L, Koch C (2005) Components of bottom-up gaze allocation in natural images. Vis Res 45:2397–2416 Rapantzikos K, Tsapatsoulis N, Avrithis Y, Kollias S (2007) Bottomup spatiotemporal visual attention model for video analysis. Image Process IET 1:237–248 Solomon SG, Lennie P (2005) Chromatic gain controls in visual cortical neurons. J Neurosci 25:4779–4792 Solomon SG, Lennie P (2007) The machinery of colour vision. Nat Rev Neurosci 8:276–286 Schluppeck D, Engel SA (2002) Color opponent neurons in V1: a review and model reconciling results from imaging and singleunit recording. J Vis 2:480–492 T’so DY, Gilbert CD (1988) The organization of chromatic and spatial interactions in the primate striate cortex. J Neurosci 8:1712–1727 Tatler BW, Hayhoe MM, Land MF, Ballard DH (2011) Eye guidance in natural vision: reinterpreting salience. J Vis 11:1–23 Treisman A, Sykes M, Gelade G (1977) Selective attention stimulus integration. Lawrence Erlbaum Associates, Hillsdale, pp 333–361 Treisman AM, Gelade G (1980) A feature-integration theory of attention. Cognit Psychol 12:97–136 Wachtler T, Sejnowski TJ, Albright TD (2003) Representation of color stimuli in awake macaque primary visual cortex. Neuron 37:681– 691 Walther D, Koch C (2006) Modeling attention to salient proto-objects. Neural Netw 19:1395–1407 |
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Ramírez Moreno, David Fernandovirtual::4317-1Ramírez Villegas, Juan Felipe45c3dbaeb005b88577208dbed7f90618Universidad Autónoma de Occidente. Calle 25 115-85. Km 2 vía Cali-Jamundí2019-11-29T15:43:43Z2019-11-29T15:43:43Z2012-09Ramirez-Villegas, J.F., Ramirez-Moreno, D.F. Color coding in the cortex: a modified approach to bottom-up visual attention. Biol Cybern 107, 39–47 (2013). https://doi.org/10.1007/s00422-012-0522-6http://red.uao.edu.co//handle/10614/11620https://doi.org/10.1007/s00422-012-0522-6Itti and Koch’s (Vision Research 40:1489–1506,2000) saliency-based visual attention model is a broadlyaccepted model that describes how attention processes aredeployed in the visual cortex in a pure bottom-up strategy.This work complements their model by modifying the colorfeature calculation. Evidence suggests that S-cone responsesare elicited in the same spatial distribution and have the samesign as responses to M-cone stimuli; these cells are tenta-tively referred to as red-cyan. For other cells, the S-coneinput seems to be aligned with the L-cone input; these cellsmight be green-magenta cells. To model red-cyan and green-magenta double-opponent cells, we implement a center-sur-round difference approach of the aforementioned model. Theresulting color maps elicited enhanced responses to colorsalient stimuli when compared to the classic ones at highstatistical significance levels. We also show that the modi-fied model improves the prediction of locations attended byhuman viewersapplication/pdfpáginas 39-47engUniversidad Autónoma de OccidenteBiological Cybernetics. Volumen 107, número 1 (September 2012); páginas 39-474739107Biological CyberneticsBergen JR, Julesz B (1983) Parallel versus serial processing in rapid pattern discrimination. Nature 303:696–698Bollman M, Hoischen R, Mertsching B (1997) In: Berlin et al (eds) Integration of static and dynamic scene features guiding visual attention. Springer, pp 483–490Burt PJ, Adelson EH (1983) The Laplacian pyramid as a compact image code. IEEE Trans Commun 31:532–540Conway BR (2001) Spatial structure of cone inputs to color cells in alert macaque primary visual cortex (V-1). J Neurosci 21:2768–2783Conway BR (2009) Color vision, cones and color-coding in the cortex. Neuroscientist 15:274–290Conway BR, Livingstone MS (2006) Spatial and temporal properties of cone signals in alert macaque primary visual cortex. J Neurosci 26:10826–10846Conway BR, Hubel DH, Livingstone MS (2002) Color contrast in macaque V1. Cereb Cortex 12:915–925De Brecht M, Saiki J (2006) A neural network implementation of a saliency map model. Neural Netw 19:1467–1474Desimone R, Duncan J (1995) Neural mechanisms of selective visual attention. Annu Rev Neurosci 18:193–222Engel S, Zhang X,Wandell B (1997) Colour tuning in human visual cortex measured with functional magnetic resonance imaging. Nature 388:68–71Fawcett T (2006) An introduction to ROC analysis. Pat Rec Lett 27:861–874Gao D, Vasconcelos N (2007) Bottom-up saliency is a discriminant process. Proceedings of the IEEE international conference on computer visión Gegenfurtner KR, Kiper DC (2003) Color vision. Annu Rev Neurosci 26:181–206Hofer H, Singer B, Williams DR (2005) Different sensations from cones with the same photopigment. J Vis 5:444–454Itti L (2000) Models of bottom-up and top-down visual attention. Dissertation, CaliforniaInstitute of Technology, Pasadena, CA Itti L (2004) Automatic foveation for video compression using a neurobiological model of visual attention. IEEE Trans Image Process 13:1304–1318Itti L, Koch C (2000) A saliency-based search mechanism for overt and covert shifts of visual attention. Vis Res 40:1489–1506Itti L, Koch C (2001) Computational modeling of visual attention. Nat Rev Neurosci 2:194–203Itti L, Koch C, Niebur E (1998) A model of saliency-based visual attention for rapid scene analysis. IEEE Trans Patt Anal Mach Intel 20:1254–1259Johnson EN, Hawken MJ, Shapley R (2001) The spatial transformation of color in the primary visual cortex of the macaque monkey. Nat Neurosci 4:409–416Koch C, Ullman S (1985) Shifts in selective visual attention: towards the underlying neural circuitry. Hum Neurobiol 4:219–227Liu T, Sun J, Zheng NN, Tang X, Shum HY (2007a) Learning to detect a salient object. Proceedings of IEEE computer society conference on computer and vision pattern recognitionLiu T, Sun J, Zheng NN, Tang X, Shum HY (2007b) MSRA Salient Object Database. Microsoft Research. http://research.microsoft.com/en-us/um/people/jiansun/salientobject/salient_object.htm. Accessed 12 June 2012Masciocchi CM, Mihalas S, Parkhurst D, Niebur E (2009) Everyone knows what is interesting: salient locations which should be fixated. J Vis 9:1–22Peters RJ, Iyer A, Itti L, Koch C (2005) Components of bottom-up gaze allocation in natural images. Vis Res 45:2397–2416Rapantzikos K, Tsapatsoulis N, Avrithis Y, Kollias S (2007) Bottomup spatiotemporal visual attention model for video analysis. Image Process IET 1:237–248Solomon SG, Lennie P (2005) Chromatic gain controls in visual cortical neurons. J Neurosci 25:4779–4792Solomon SG, Lennie P (2007) The machinery of colour vision. Nat Rev Neurosci 8:276–286Schluppeck D, Engel SA (2002) Color opponent neurons in V1: a review and model reconciling results from imaging and singleunit recording. J Vis 2:480–492T’so DY, Gilbert CD (1988) The organization of chromatic and spatial interactions in the primate striate cortex. J Neurosci 8:1712–1727Tatler BW, Hayhoe MM, Land MF, Ballard DH (2011) Eye guidance in natural vision: reinterpreting salience. J Vis 11:1–23Treisman A, Sykes M, Gelade G (1977) Selective attention stimulus integration. Lawrence Erlbaum Associates, Hillsdale, pp 333–361Treisman AM, Gelade G (1980) A feature-integration theory of attention. Cognit Psychol 12:97–136Wachtler T, Sejnowski TJ, Albright TD (2003) Representation of color stimuli in awake macaque primary visual cortex. Neuron 37:681– 691Walther D, Koch C (2006) Modeling attention to salient proto-objects. 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