Abstract
This paper proposes a novel approach to construct saliency map of color contrast and an enhanced technique for inhibition of return on this map for artificial visual attention. The ability to handle dynamic scenes is also included in the model by introducing a memory based mechanism. For the process of color map construction the traditionally followed concept of double-opponent colors is extended by implementing the concepts of contrast from the subject of color theory. In context of inhibition of return, the color based inhibition is also modeled according to recent research in human vision apart from the commonly implemented spatial inhibition. The proposed methods have produced results compatible with the existing models of visual attention whereas the region-based nature of the proposed technique renders advantages of precise localization of the foci of attention, proper representation of the shapes of the attended objects, and accelerated computation time.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Law, M.B., Pratt, J., Abrams, R.A.: Color-based inhibition of return. Perception & Psychophysics, 402–408 (1995)
Itti, L., Koch, C.: A saliency based search mechanism for overt and covert shifts of visual attention. Vision Research, 1489–1506 (2000)
Rutishauser, U., Walther, D., Koch, C., Perona, P.: Is bottom-up attention useful for object recognition? In: IEEE International Conference on Computer Vision and Pattern Recognition, Washington DC, pp. 37–44 (2004)
Engel, S., Zhang, X., Wandell, B.: Color tuning in human visual cortex measured with functional magnetic resonance imaging. Nature 388, 68–71 (1997)
Aziz, M.Z., Mertsching, B.: Color segmentation for a region-based attention model. In: Farbworkshop 2006, Ilmenau - Germany, pp. 74–83 (2006)
Aziz, M.Z., Mertsching, B., Shafik, M.S., Stemmer, R.: Evaluation of visual attention models for robots. In: ICVS 2006, IEEE, New York - USA (2006)
Aziz, M.Z., Stemmer, R., Mertsching, B.: Region-based depth feature map for visual attention in autonomous mobile systems. In: AMS 2005, Stuttgart - Germany, Informatik Aktuell, pp. 89–95. Springer, Heidelberg (2005)
Aziz, M.Z., Mertsching, B.: Pop-out and IOR in static scenes with region based visual attention. In: WCAA-ICVS 2007, Bielefeld University eCollections, Bielefeld - Germany (2007)
Aziz, M.Z., Mertsching, B.: Color saliency and inhibition in region based visual attention. In: WAPCV 2007, Hyderabad - India, pp. 95–108 (2007)
Itti, L., Koch, U., Niebur, E.: A model of saliency-based visual attention for rapid scene analysis. Transactions on Pattern Analysis and Machine Intelligence 20, 1254–1259 (1998)
Sun, Y., Fischer, R.: Object-based visual attention for computer vision. Artificial Intelligence 146, 77–123 (2003)
Park, S.J., Ban, S.J., Sang, S.W., Shin, J.K., Lee, M.: Implementation of visual attention system using bottom-up saliency map model. In: Kaynak, O., Alpaydın, E., Oja, E., Xu, L. (eds.) ICANN 2003 and ICONIP 2003. LNCS, vol. 2714, pp. 678–685. Springer, Heidelberg (2003)
Meur, O.L., Callet, P.L., Barba, D., Thoreau, D.: A coherent computational approach to model bottom-up visual attention. Transactions on Pattern Analysis and Machine Intelligence 28, 802–817 (2006)
Stentiford, F.: An estimator for visual attention through competitive novelty with application to image compression. In: Picture Coding Symposium, Seoul - Korea, pp. 101–104 (2001)
Backer, G., Mertsching, B., Bollmann, M.: Data- and model-driven gaze control for an active-vision system. Transactions on Pattern Analysis and Machine Intelligence 23, 1415–1429 (2001)
Frintrop, S., Backer, G., Rome, E.: Goal-directed search with a top-down modulated computational attention system. In: Kropatsch, W.G., Sablatnig, R., Hanbury, A. (eds.) DAGM 2005. LNCS, vol. 3663, pp. 117–124. Springer, Heidelberg (2005)
Dankers, A., Barnes, N., Zelinsky, A.: A reactive vision system: Active-dynamic saliency. In: ICVS 2007, Bielefeld University, Bielefeld, Germany (2007)
Atsumi, M.: Stochastic attentional selection and shift on the visual attention pyramid. In: ICVS 2007, Bielefeld - Germany (2007)
Ford, J.L.: Internet Resource (2006), http://www.worqx.com
Itten, J.: The Elements of Color. John Wiley & Sons Inc., New York, USA (1961)
Mahnke, F.: Color, Environment, and Human Response. Van Nostrand Reinhold, Detroit (1996)
Goolsby, B.A., Grabowecky, M., Suzuki, S.: Adaptive modulation of color salience contingent upon global form coding and task relevance. Vision Research, 901–930 (2005)
Cutzua, F., Tsotsos, J.K.: The selective tuning model of attention: Psychophysical evidence for a suppressive annulus around an attended item. Vision Research, 205–219 (2003)
Aziz, M.Z., Mertsching, B.: An attentional approach for perceptual grouping of spatially distributed patterns. In: Hamprecht, F.A., Schnörr, C., Jähne, B. (eds.) DAGM 2007. LNCS, vol. 4713, pp. 345–354. Springer, Heidelberg (2007)
Frintrop, S., Klodt, M., Rome, E.: A real-time visual attention system using integral images. In: ICVS 2007, Bielefeld University eCollections, Bielefeld - Germany (2007)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2007 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Aziz, M.Z., Mertsching, B. (2007). Color Saliency and Inhibition Using Static and Dynamic Scenes in Region Based Visual Attention. In: Paletta, L., Rome, E. (eds) Attention in Cognitive Systems. Theories and Systems from an Interdisciplinary Viewpoint. WAPCV 2007. Lecture Notes in Computer Science(), vol 4840. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77343-6_15
Download citation
DOI: https://doi.org/10.1007/978-3-540-77343-6_15
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-77342-9
Online ISBN: 978-3-540-77343-6
eBook Packages: Computer ScienceComputer Science (R0)