| Title | Semantic 3-D labeling of ear implants using a global parametric transition prior |
| Publication Type | Conference Paper |
| Year of Publication | 2015 |
| Authors | Zouhar, A, Rother, C, Fuchs, S |
| Conference Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
| ISBN Number | 9783319245706 |
| Abstract | In this work we consider the problem of sematic part-labeling of 3-D meshesof ear implants. This is a challenging problem and automatic solutions are of high practical relevance, since they help to automate the design of hearing aids. The contribution of this work is a new framework which outperforms existing approaches for this task. To achieve the boost in performance we introduce the new concept of a global parametric transition prior. To our knowledge, this is the first time that such a generic prior is used for 3-D mesh processing, and it may be found useful for a large class of 3-D meshes. To foster more research on the important topic of ear implant labeling, we collected a large data set of 3-D meshes, with associated ground truth labels, which we will make publicly available. |
| DOI | 10.1007/978-3-319-24571-3_22 |
| Citation Key | Zouhar2015 |
