Interaction-Driven Active 3D Reconstruction with Object Interiors
Zihao Yan Fubao Su Mingyang Wang Ruizhen Hu Hao Zhang Hui Huang
We introduce an active 3D reconstruction method which integrates visual
perception, robot-object interaction, and 3D scanning to recover both the
exterior and interior, i.e., unexposed, geometries of a target 3D object.
Unlike other works in active vision which focus on optimizing camera viewpoints
to better investigate the environment, the primary feature of our
reconstruction is an analysis of the interactability of various parts of the
target object and the ensuing part manipulation by a robot to enable scanning
of occluded regions. As a result, an understanding of part articulations of the
target object is obtained on top of complete geometry acquisition. Our method
operates fully automatically by a Fetch robot with built-in RGBD sensors. It
iterates between interaction analysis and interaction-driven reconstruction,
scanning and reconstructing detected moveable parts one at a time, where both
the articulated part detection and mesh reconstruction are carried out by
neural networks. In the final step, all the remaining, non-articulated parts,
including all the interior structures that had been exposed by prior part
manipulations and subsequently scanned, are reconstructed to complete the
acquisition. We demonstrate the performance of our method via qualitative and
quantitative evaluation, ablation studies, comparisons to alternatives, as well
as experiments in a real environment.