Object Modelling with a Handheld RGB-D Camera

TL;DR

This paper introduces a flexible RGB-D based system for reconstructing full 3D object models from multiple partial scans, suitable for various applications without constraints on object appearance or setup.

Contribution

The system enables automatic merging of partial 3D scans into complete models and integrates with recognition and tracking modules for enhanced object perception.

Findings

Reconstructed accurate and visually appealing 3D models

Supports various object appearances and acquisition setups

Facilitates object recognition and tracking applications

Abstract

This work presents a flexible system to reconstruct 3D models of objects captured with an RGB-D sensor. A major advantage of the method is that our reconstruction pipeline allows the user to acquire a full 3D model of the object. This is achieved by acquiring several partial 3D models in different sessions that are automatically merged together to reconstruct a full model. In addition, the 3D models acquired by our system can be directly used by state-of-the-art object instance recognition and object tracking modules, providing object-perception capabilities for different applications, such as human-object interaction analysis or robot grasping. The system does not impose constraints in the appearance of objects (textured, untextured) nor in the modelling setup (moving camera with static object or a turn-table setup). The proposed reconstruction system has been used to model a large number of objects resulting in metrically accurate and visually appealing 3D models.