2014 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2014)
Columbus, OH, USA
June 23, 2014 to June 28, 2014
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/CVPR.2014.500
We describe a simple and fast algorithm for optimizing Markov random fields over images. The algorithm performs block coordinate descent by optimally updating a horizontal or vertical line in each step. While the algorithm is not as accurate as state-of-the-art MRF solvers on traditional benchmark problems, it is trivially parallelizable and produces competitive results in a fraction of a second. As an application, we develop an approach to increasing the accuracy of consumer depth cameras. The presented algorithm enables high-resolution MRF optimization at multiple frames per second and substantially increases the accuracy of the produced range images.
Heuristic algorithms, Optimization, Image reconstruction, Cameras, Accuracy, Speckle, Correlation
Q. Chen and V. Koltun, "Fast MRF Optimization with Application to Depth Reconstruction," 2014 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Columbus, OH, USA, 2014, pp. 3914-3921.