Convex Optimization for Scene Understanding
| Title | Convex Optimization for Scene Understanding |
| Publication Type | Conference Paper |
| Year of Publication | 2013 |
| Authors | Souiai, M., Nieuwenhuis C., Strekalovskiy E., & Cremers D. |
| Other Numbers | 3625 |
| Abstract | In this paper we give a convex optimization approach forscene understanding. Since segmentation, object recognition and scene labeling strongly benefit from each other wepropose to solve these tasks within a single convex optimization problem. In contrast to previous approaches we do notrely on pre-processing techniques such as object detectorsor superpixels. The central idea is to integrate a hierarchical label prior and a set of convex constraints into thesegmentation approach, which combine the three tasks byintroducing high-level scene information. Instead of learning label co-occurrences from limited benchmark trainingdata, the hierarchical prior comes naturally with the wayhumans see their surroundings. |
| Acknowledgment | This work was partially funded by the Deutscher Akademischer Austausch Dienst (DAAD) through a postdoctoral fellowship. |
| URL | http://www.icsi.berkeley.edu/pubs/vision/convexoptimization13.pdf |
| Bibliographic Notes | Proceedings of the Workshop on Graphical Models for Scene Understanding at the International Conference on Computer Vision 2013 (ICCV 2013), Sydney, Australia |
| Abbreviated Authors | M. Souiai, C. Nieuwenhuis, E. Strekalovskiy, and D. Cremers |
| ICSI Research Group | Vision |
| ICSI Publication Type | Article in conference proceedings |