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2018 | OriginalPaper | Buchkapitel

Salient Spin Images: A Descriptor for 3D Object Recognition

verfasst von : Jihad H’roura, Michaël Roy, Alamin Mansouri, Driss Mammass, Patrick Juillion, Ali Bouzit, Patrice Méniel

Erschienen in: Image and Signal Processing

Verlag: Springer International Publishing

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Abstract

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%.

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Metadaten
Titel
Salient Spin Images: A Descriptor for 3D Object Recognition
verfasst von
Jihad H’roura
Michaël Roy
Alamin Mansouri
Driss Mammass
Patrick Juillion
Ali Bouzit
Patrice Méniel
Copyright-Jahr
2018
DOI
https://doi.org/10.1007/978-3-319-94211-7_26