Dense Two-Frame Stereo Correspondence by Self-organizing Neural Network

Authors:
Marco Vanetti;Ignazio Gallo;Elisabetta Binaghi
Affiliations:
Department of Computer Science and Communication, Università degli Studi dell'Insubria, Varese, Italy;Department of Computer Science and Communication, Università degli Studi dell'Insubria, Varese, Italy;Department of Computer Science and Communication, Università degli Studi dell'Insubria, Varese, Italy
Venue:
ICIAP '09 Proceedings of the 15th International Conference on Image Analysis and Processing
Year:
2009

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Abstract

This work aims at defining an extension of a competitive method for matching correspondences in stereoscopic image analysis. The method we extended was proposed by Venkatesh, Y.V. et al where the authors extend a Self-Organizing Map by changing the neural weights updating phase in order to solve the correspondence problem within a two-frame area matching approach and producing dense disparity maps. In the present paper we have extended the method mentioned by adding some details that lead to better results. Experimental studies were conducted to evaluate and compare the solution proposed.