Title :
An epipolar-constrained prior for efficient search in multi-view scenarios
Author :
Bosch, Ignacio ; Salvador, Jordi ; Perez-Pellitero, Eduardo ; Ruiz-Hidalgo, Javier
Abstract :
In this paper we propose a novel framework for fast exploitation of multi-view cues with applicability in different image processing problems. In order to bring our proposed framework into practice, an epipolar-constrained prior is presented, onto which a random search algorithm is proposed to find good matches among the different views of the same scene. This algorithm includes a generalization of the local coherency in 2D images for multi-view wide-baseline cases. Experimental results show that the geometrical constraint allows a faster initial convergence when finding good matches. We present some applications of the proposed framework on classical image processing problems.
Keywords :
image processing; 2D images; approximate nearest neighbor; deblurring; epipolar line; epipolar-constrained prior; image processing; random search algorithm; super resolution; Cameras; Computer vision; Image reconstruction; Image resolution; PSNR; Proposals; Super resolution; approximate nearest neighbor; deblurring; epipolar line;
Conference_Titel :
Signal Processing Conference (EUSIPCO), 2014 Proceedings of the 22nd European
Conference_Location :
Lisbon