Abstract
In this paper, we propose a new saliency map model to find a selective attention region in a static color image for human-like fast scene analysis. We consider the roles of cells in our visual receptor for edge detection and cone opponency, and also reflect the roles of the lateral geniculate nucleus to find a symmetrical property of an interesting object such as shape and pattern. Also, independent component analysis (ICA) is used to find a filter that can generate a salient region from feature maps constructed by edge, color opponency and symmetry information, which models the role of redundancy reduction in the visual cortex. Computer experimental results show that the proposed model successfully generates the plausible sequence of salient region.
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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) (1998) 1254–1259
Yagi, T., Asano, N., Makita, S., Uchikawa, Y.: Active vision inspired by mammalian fixation mechanism. Intelligent Robots and Systems (1995) 39–47
Treisman, Gelde, G., A. M.: A feature-intergation theory of attention. Cognitive Psychology 12(1) (1980) 97–136
Barlow, H. B., Tolhust, D. J.: Why do you have edge detectors? Optical society of America Technical Digest. 23 (1992) 172
Bell, A. J., Sejnowski, T. J.: The independent components of natural scenes are edge filters. Vision Research. 37 (1997) 3327–3338
Buchsbaum, G., Gottschalk, A.: Trichromacy, opponent colours coding and optimum colour information transmission in the retina. Proc. R. Soc. London Ser. B 220 (1983) 89–113
Wachtler, T., Lee, T. W., Sejnowski, T. J.: Chromatic structure of natural scenes. J. Opt. Soc. Am. A, Vol. 18 (2001) No. 1
Bruce Goldstein E.: Sensation and Perception. 4th edn. An international Thomson publishing company, USA (1995)
Majani, E., Erlanson, R., Abu-Mostafa, Y.: The Eye. Academic, New York (1984)
Kuffler, S. W., Nicholls, J. G., Martin, J. G.: From Neuron to Brain. Sinauer Associates, Sunderland, U.K (1984)
Gonzalez, R. G., Woods, R. E.: Digital Image Processing. Addison-Wesley Publishing Company, USA (1993)
Lee, T. W.: Independent Component Analysis-theory and application. Kluwer academic publisher, (1998)
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. Vol. E84-A. Jun. (2001) No. 6
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Park, SJ., Shin, JK., Lee, M. (2002). Biologically Inspired Saliency Map Model for Bottom-up Visual Attention. In: Bülthoff, H.H., Wallraven, C., Lee, SW., Poggio, T.A. (eds) Biologically Motivated Computer Vision. BMCV 2002. Lecture Notes in Computer Science, vol 2525. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36181-2_42
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DOI: https://doi.org/10.1007/3-540-36181-2_42
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