Three-dimensional computer vision: a geometric viewpoint
Three-dimensional computer vision: a geometric viewpoint
Hybrid-maximum neural network for depth analysis from stereo-image
ICAISC'10 Proceedings of the 10th international conference on Artifical intelligence and soft computing: Part II
A novel continuous dual mode neural network in stereo-matching process
ICANN'10 Proceedings of the 20th international conference on Artificial neural networks: Part III
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In the present thesis the author undertakes the problem of the objects selecting on pictures. The novel conception of using depth map as a base to objects marking was proposed here. objects separation can be done on the base of depth (disparity), corresponding to points that should be marked. This allows for elimination of textures, occurring in background and also on objects. The object selection process must be preceded by picture's depth analysis. This can be done by the novel neural structure: Self-Correcting Neural Network. This structure is working point-by-point with no picture's segmentation before.