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. © 2009 Springer Berlin Heidelberg.
CITATION STYLE
Vanetti, M., Gallo, I., & Binaghi, E. (2009). Dense two-frame stereo correspondence by self-organizing neural network. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5716 LNCS, pp. 1035–1042). https://doi.org/10.1007/978-3-642-04146-4_110
Mendeley helps you to discover research relevant for your work.