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

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 SelfOrganizing 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. Key words: Stereo matching, self-organizing map, disparity map, occlusions

• Type: Conference
• Year: 2009
• Where: ICIAP
• Authors: Marco Vanetti, Ignazio Gallo, Elisabetta Binaghi
• Keywords: Area Matching Approach, Dense Disparity Maps, Disparity Map, ICIAP 2009, Image Processing