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Acknowledgements. This work was supported by the Sino-German Research Training
Group CINACS, DFG GRK 1247/1 and 1247/2, and by the EU projects KSERA un-
der 2010-248085 and eSMCs under ICT-270212. We thank R. Cuijpers and C. Weber
for inspiring and very helpful discussions, S. Heinrich, D. Jessen and N. Navarro for
assistance with the robot.
References
1. O'Regan, J.K., Noe, A.: A sensorimotor account of vision and visual consciousness. Behav.
Brain Sci. 24(5) (October 2001); 939-73; discussion 973-1031
2. Dill, M., Wolf, R., Heisenberg, M.: Visual pattern recognition in drosophila involves retino-
topic matching. Nature 365(6448), 751-753 (1993)
3. Franceschini, N.: Combined optical, neuroanatomical, electrophysiological and behavioral
studies on signal processing in the fly compound eye. In: Taddei-Ferretti, C. (ed.) Biocy-
bernetics of Vision: Integrative Mechanisms and Cognitive Processes: Proceedings of the
International School of Biocybernetics, Casamicciola, Napoli, Italy, October 16-22, 1994,
vol. 2, World Scientific, Singapore (1997)
4. Steinman, S.B., Steinman, B.A., Garzia, R.P.: Foundations of binocular vision: a clinical
perspective. McGraw-Hill, New York (2000)
5. Pfeifer, R., Lungarella, M., Iida, F.: Self-organization, embodiment, and biologically inspired
robotics. Science 318(5853), 1088-1093 (2007)
6. Tani, J., Ito, M.: Self-organization of behavioral primitives as multiple attractor dynamics:
A robot experiment. IEEE Transactions on Systems, Man and Cybernetics, Part A: Systems
and Humans 33(4), 481-488 (2003)
7. Tani, J., Ito, M., Sugita, Y.: Self-organization of distributedly represented multiple be-
havior schemata in a mirror system: reviews of robot experiments using RNNPB. Neural
Netw. 17(8-9), 1273-1289 (2004)
8. Cuijpers, R.H., Stuijt, F., Sprinkhuizen-Kuyper, I.G.: Generalisation of action sequences in
RNNPB networks with mirror properties. In: Proceedings of the 17th European symposium
on Artifical Neural Networks (ESANN), pp. 251-256 (2009)
9. Kolen, J.F., Kremer, S.C.: A field guide to dynamical recurrent networks. IEEE Press, New
York (2001)
10. Riedmiller, M., Braun, H.: A direct adaptive method for faster backpropagation learning:
the RPROP algorithm. In: IEEE International Conference on Neural Networks, vol. 1, pp.
586-591 (1993)
11. LeCun, Y.A., Bottou, L., Orr, G.B., Muller, K.-R.: Efficient BackProp. In: Orr, G.B., Muller,
K.-R. (eds.) NIPS-WS 1996. LNCS, vol. 1524, pp. 9-50. Springer, Heidelberg (1998)
12. Bradski, G.: The OpenCV Library. Dr. Dobb's Journal of Software Tools (2000)
13. Suzuki, S., Be, K.: Topological structural analysis of digitized binary images by border fol-
lowing. Computer Vision, Graphics, and Image Processing 30(1), 32-46 (1985)
14. Hu, M.K.: Visual pattern recognition by moment invariants. IRE Transactions on Information
Theory 8(2), 179-187 (1962)
15. Chang, C.C., Lin, C.J.: LIBSVM: A library for support vector machines. ACM Transactions
on Intelligent Systems and Technology 2, 27:1-27:27 (2011)
16. Kleesiek, J., Badde, S., Wermter, S., Engel, A.K.: What do Objects Feel Like? Active Percep-
tion for a Humanoid Robot. In: Proceedings of the 4th International Conference on Agents
and Artificial Intelligence (ICAART), vol. 1, pp. 64-73 (2012)
17. Meltzoff, A.N., Meltzoff, A.N., Moore, M.K.: Explaining facial imitation: a theoretical
model. Early Development and Parenting 6, 179-192 (1997)
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