@conference {Baldassarri2003368,
	title = {Visual self-localisation using automatic topology construction},
	booktitle = {Proceedings - 12th International Conference on Image Analysis and Processing, ICIAP 2003},
	year = {2003},
	note = {cited By 0},
	pages = {368-374},
	abstract = {The paper proposes a machine learning method for self-localising a mobile agent, using the images supplied by a single omni-directional camera. The images acquired by the camera may be viewed as an implicit topological representation of the environment. The environment is a priori unknown and the topological representation is derived by unsupervised neural network architecture. The architecture includes a self-organising neural network, and is constituted by a growing neural gas, which is well known for its topology preserving quality. The growth depends on the topology that is not a priori defined, and on the need of discovering it, by the neural network, during the learning. The implemented system is able to recognise correctly the input frames and to reconstruct a topological map of the environment. Each node of the neural network identifies a single zone of the environment and the connections between the nodes correspond to the real space connections in the environment. {\textcopyright} 2003 IEEE.},
	doi = {10.1109/ICIAP.2003.1234077},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-84890545853\&partnerID=40\&md5=6954a4c9b47cdb3e275eac96afdf95a2},
	author = {Paola Baldassarri and Paolo Puliti and A. Montesanto and Guido Tascini}
}
