| Full text | |
| Author(s): |
Andalo, Fernanda A.
;
Taubin, Gabriel
;
Goldenstein, Siome
Total Authors: 3
|
| Document type: | Journal article |
| Source: | IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE; v. 39, n. 2, p. 385-396, FEB 2017. |
| Web of Science Citations: | 9 |
| Abstract | |
In this article we present the first effective method based on global optimization for the reconstruction of image puzzles comprising rectangle pieces-Puzzle Solving by Quadratic Programming (PSQP). The proposed novel mathematical formulation reduces the problem to the maximization of a constrained quadratic function, which is solved via a gradient ascent approach. The proposed method is deterministic and can deal with arbitrary identical rectangular pieces. We provide experimental results showing its effectiveness when compared to state-of-the-art approaches. Although the method was developed to solve image puzzles, we also show how to apply it to the reconstruction of simulated strip-shredded documents, broadening its applicability. (AU) | |
| FAPESP's process: | 12/50468-6 - Vision for the blind: translating 3D visual concepts into 3D auditory clues |
| Grantee: | Siome Klein Goldenstein |
| Support Opportunities: | Research Grants - Research Partnership for Technological Innovation - PITE |