GBOT: Graph-Based 3D Object Tracking for Augmented Reality-Assisted
  Assembly Guidance
Shiyu Li Hannah Schieber Niklas Corell Bernhard Egger Julian Kreimeier Daniel Roth
Guidance for assemblable parts is a promising field for augmented reality.
Augmented reality assembly guidance requires 6D object poses of target objects
in real time. Especially in time-critical medical or industrial settings,
continuous and markerless tracking of individual parts is essential to
visualize instructions superimposed on or next to the target object parts. In
this regard, occlusions by the user's hand or other objects and the complexity
of different assembly states complicate robust and real-time markerless
multi-object tracking. To address this problem, we present Graph-based Object
Tracking (GBOT), a novel graph-based single-view RGB-D tracking approach. The
real-time markerless multi-object tracking is initialized via 6D pose
estimation and updates the graph-based assembly poses. The tracking through
various assembly states is achieved by our novel multi-state assembly graph. We
update the multi-state assembly graph by utilizing the relative poses of the
individual assembly parts. Linking the individual objects in this graph enables
more robust object tracking during the assembly process. For evaluation, we
introduce a synthetic dataset of publicly available and 3D printable assembly
assets as a benchmark for future work. Quantitative experiments in synthetic
data and further qualitative study in real test data show that GBOT can
outperform existing work towards enabling context-aware augmented reality
assembly guidance. Dataset and code will be made publically available.