In this paper, a novel framework for dense pixel matching based on dynamic programming is introduced. Unlike most techniques proposed in the literature, our approach assumes neither known camera geometry nor the availability of rectified images. Under such conditions, the matching task cannot be reduced to finding correspondences between a pair of scanlines. We propose to extend existing dynamic programming methodologies to a larger dimensional space by using a 3D scoring matrix so that correspondences between a line and a whole image can be calculated. After assessing our framework on a standard evaluation dataset of rectified stereo images, experiments are conducted on unrectified and non-linearly distorted images. Results validate our new approach and reveal the versatility of our algorithm.
|Title of host publication||VISAPP 2012 - Proceedings of the International Conference on Computer Vision Theory and Applications|
|Number of pages||9|
|Publication status||Published - 01 Jan 2012|
ASJC Scopus subject areas
- Computer Graphics and Computer-Aided Design
- Computer Vision and Pattern Recognition
Thevenon, J., Martinez-Del-Rincon, J., Dieny, R., & Nebel, J-C. (2012). Dense pixel matching between unrectified and distorted images using dynamic programming. In VISAPP 2012 - Proceedings of the International Conference on Computer Vision Theory and Applications (Vol. 2, pp. 216-224)