Abstract
A computational theory concept generating saliency maps from feature maps generated in the bottom-up using various filters such as Fourier transformation was discussed. We proposed saliency map related to motion based on self-organized feature extracting not using general filter such as Fourier transform. We introduce the ICA base function to realize the self-organized Saliency Map. We extend the ICA base function estimation to apply for the non-uniform positioned photoreceptor cells which receives the current image and the previous image to get the motion information. We show the effectiveness of our model by applying this model for real images.
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References
Marr, D.: VISION. WHF Freeman and Company, New York (1982)
Koch, C., Ullman, S.: Shifts in selective visual-attention towards the underlying neural circuitry. Hum. Neurobiol. 4, 219–227 (1985)
Itti, L., Koch, C.: Feature combination strategies for saliency-based visual attention systems. J. Electron Imaging 10(1), 161–169 (2001)
Mallet, S.G.: A theory for multiresolution signal decomposition: The wavelet representation. IEEE Tran. on PAMI 11, 674–693 (1989)
Hyvarinen, A., Hoyer, P.O.: Emergence of phase and shift invariant features by decomposition of natural images into independent feature subspace. Neural Computation 12(7), 1705–1720 (2000)
Hubel, D.H., Wiesel, T.N.: Receptive fields, binocular interaction and functional architecture in the cat’s visual cortex. J. Physiol. 160, 106–154 (1962)
Blakemore, C., Cooper, G.F.: Development of the brain depends on the visual environment. Nature 228, 477–478 (1970)
von der Malsburg, C.: Self-organization of orientation sensitive cells in the striate cortex. Kybernetik 14, 85–100 (1973)
Willshaw, D.J., von der Malsburg, C.: How patterned neural connections can be set up by self-organization. Proc. R. Soc. Land. B. 194, 431–445 (1976)
Kohonen, T.: Self-organized formation of topographically corerct feature maps. Biol. Cybern. 43, 59–69 (1982)
Horn, B.K., Schunck, B.G.: Determining optical flow. Artif. Intell. 17, 185–203 (1981)
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Morita, S. (2009). Generating Saliency Map Related to Motion Based on Self-organized Feature Extracting. In: Köppen, M., Kasabov, N., Coghill, G. (eds) Advances in Neuro-Information Processing. ICONIP 2008. Lecture Notes in Computer Science, vol 5507. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03040-6_96
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DOI: https://doi.org/10.1007/978-3-642-03040-6_96
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