Abstract
In this paper, we propose a trainable selective attention model that can not only inhibit an unwanted salient area but also reinforce an interesting area. The proposed model was implemented by the bottom-up saliency map model in conjunction with the top-down attention mechanism. The bottom-up saliency map model generates a salient area, and human supervisor decides whether the selected salient area is inhibited or reinforced. The fuzzy adaptive resonance theory (Fuzzy-ART) network can generate an inhibit signal or a reinforcement signal so that the sequence of attention areas is modified to be a desired scan path. Computer simulation results show that the proposed model successfully generates the plausible scan path of salient region.
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
Itti, L., Koch, C., Niebur, E.: A model of saliency-based visual attention for rapid scene analysis. IEEE Trans. Patt. Anal. Mach. Intell. 20(11), 1254–1259 (1998)
Koike, T., Saiki, J.: Stochastic guided search model for search asymmetries in visual search tasks. In: Bülthoff, H.H., Lee, S.-W., Poggio, T.A., Wallraven, C. (eds.) BMCV 2002. LNCS, vol. 2525, pp. 408–417. Springer, Heidelberg (2002)
Sun, Y., Fisher, R.B.: Hierarchical selectivity for object-based visual attention. In: Bülthoff, H.H., Lee, S.-W., Poggio, T.A., Wallraven, C. (eds.) BMCV 2002. LNCS, vol. 2525, pp. 427–438. Springer, Heidelberg (2002)
Bruce Goldstein, E.: Sensation and Perception, 4th edn. An international Thomson publishing company, USA (1995)
Park, S.J., An, K.H., Lee, M.: Saliency map model with adaptive masking based on independent component analysis. Neurocomputing 49, 417–422 (2002)
Seo, K.S., Park, C.J., Cho, S.H., Choi, H.M.: Context-Free Marker-Controlled Watershed Transform for Efficient Multi-Object Detection and Segmentation. IEICE Trans. E84- A(6), 1066–1074 (2001)
Bell, A.J., Sejnowski, T.J.: The independent components of natural scenes are edge filters. Vision Research 37, 3327–3338 (1997)
Barlow, H.B., Tolhust, D.J.: Why do you have edge detectors? Optical society of America Technical Digest 23, 172 (1992)
Frank, T., Kraiss, K.F., Kuklen, T.: Comparative analysis of Fuzzy ART and ART-2A network clustering performance. IEEE Trans. Neural Networks 9(3), 544–559 (1998)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2004 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Choi, SB., Ban, SW., Lee, M. (2004). Human-Like Selective Attention Model with Reinforcement and Inhibition Mechanism. In: Pal, N.R., Kasabov, N., Mudi, R.K., Pal, S., Parui, S.K. (eds) Neural Information Processing. ICONIP 2004. Lecture Notes in Computer Science, vol 3316. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30499-9_106
Download citation
DOI: https://doi.org/10.1007/978-3-540-30499-9_106
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-23931-4
Online ISBN: 978-3-540-30499-9
eBook Packages: Springer Book Archive