3D scene reconstruction and object recognition for indoor scene

Yangping Shen; Yoshitsugu Manabe; Noriko Yata

doi:10.1117/12.2521492

22 March 2019 3D scene reconstruction and object recognition for indoor scene

Yangping Shen, Yoshitsugu Manabe, Noriko Yata

Proceedings Volume 11049, International Workshop on Advanced Image Technology (IWAIT) 2019; 1104909 (2019) https://doi.org/10.1117/12.2521492
Event: 2019 Joint International Workshop on Advanced Image Technology (IWAIT) and International Forum on Medical Imaging in Asia (IFMIA), 2019, Singapore, Singapore

Abstract

In recent years, many SLAM (simultaneous localization and mapping) systems have appeared showing impressive dense scene reconstruction. However, the normal SLAM system build 3D scenes at point level without any semantic information. Many computer vision applications require high ability of scene understanding and point-based SLAM shows insufficiency in these applications. This paper studies about fusing 3D object recognition into SLAM system, using hand-held RGB-D camera and RTAB-Map to reconstruct dense point cloud of 3D indoor scene. Then we use supervoxel based point cloud segmentation approaches to over-segment the scene. 3D object classification model trained by PointNet is added to merge the segmentation process and object recognition. Our experiment on indoor environment shows the effectiveness of this system.

Citation Download Citation

Yangping Shen, Yoshitsugu Manabe, and Noriko Yata "3D scene reconstruction and object recognition for indoor scene", Proc. SPIE 11049, International Workshop on Advanced Image Technology (IWAIT) 2019, 1104909 (22 March 2019); https://doi.org/10.1117/12.2521492

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