Salient Spin Images: A Descriptor for 3D Object Recognition
| Affiliation auteurs | !!!! Error affiliation !!!! |
| Titre | Salient Spin Images: A Descriptor for 3D Object Recognition |
| Type de publication | Conference Paper |
| Year of Publication | 2018 |
| Auteurs | H'roura J, Roy M, Mansouri A, Mammass D, Juillion P, Bouzit A, Meniel P |
| Editor | Mansouri A, Elmoataz A, Nouboud F, Mammass D |
| Conference Name | IMAGE AND SIGNAL PROCESSING (ICISP 2018) |
| Publisher | European Assoc Image & Signal Proc; Int Assoc Pattern Recognit |
| Conference Location | GEWERBESTRASSE 11, CHAM, CH-6330, SWITZERLAND |
| ISBN Number | 978-3-319-94211-7; 978-3-319-94210-0 |
| Mots-clés | 3D object recognition, Clutter, DoG, Occlusion, Salient vertex spin image, True positives |
| Résumé | In the last decades a wide range of algorithms have been devoted to recognize 3D free-from objects under real conditions such as occlusions, clutters, rotation, scale and translation. Spin image is one of these algorithms known to be robust to rotation, translation, occlusions up to 70% and clutters up to 60%, but still suffer from scaling, resolution changes and it is time consuming. In this paper we present a novel approach based on spin images, called salient spin images (SSI). This method enhances spin images algorithm based on its limits. Particularly, it decreases significantly the complexity of the algorithm using DoG detector, it shows a higher performance due to the relevant localization of salient vertices on the scene, and its robustness to occlusions reaches 80%. |
| DOI | 10.1007/978-3-319-94211-7_26 |