6-DoF Pose Estimation and CAD Model Retrieval for XR Interface from a Single RGB Image

被引：0

作者：

Park, Sieun ^{[1
]}

Jeong, Wonje ^{[1
]}

Park, Soon-Yong ^{[1
]}

机构：

[1] Kyungpook Natl Univ, Sch Elect & Elect Engn, Daegu, South Korea

来源：

PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON ADVANCED VISUAL INTERFACES, AVI 2024 | 2024年

关键词：

pose estimation; similarity measure; deep learning; AR/XR;

D O I：

10.1145/3656650.3656719

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper proposes a 6-DoF pose estimation and CAD model retrieval for XR interface from a single RGB image. A deep learning network is used to estimate the 6-DoF pose of a real object in an RGB image. Then, several CAD model candidates are rendered and their similarity with the image is measured to decide the final matching CAD model. In the last, the rendered image of the matching CAD model is overlayed with the RGB image. In the experiment, total ten object categories are tested and evaluated using two deep networks.

引用

页数：3

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