Incremental Object Database: Building 3D Models from Multiple Partial Observations

Collecting 3D object data sets involves a large amount of manual work and is time consuming. Getting complete models of objects either requires a 3D scanner that covers all the surfaces of an object or one needs to rotate it to completely observe it. We present a system that incrementally builds a database of objects as a mobile agent traverses a scene. Our approach requires no prior knowledge of the shapes present in the scene. Object-like segments are extracted from a global segmentation map, which is built online using the input of segmented RGB-D images. These segments are stored in a database, matched among each other, and merged with other previously observed instances. This allows us to create and improve object models on the fly and to use these merged models to reconstruct also unobserved parts of the scene. The database contains each (potentially merged) object model only once, together with a set of poses where it was observed. We evaluate our pipeline with one public dataset, and on a newly created Google Tango dataset containing four indoor scenes with some of the objects appearing multiple times, both within and across scenes.

Authors

• Fadri Furrer
• Tonci Novkovic
• Marius Fehr
• Abel Gawel
• Margarita Grinvald
• Torsten Sattler
• Roland Siegwart
• Juan I. Nieto 0001

Keywords

• Image segmentation
• Databases
• Three-dimensional displays
• GSM
• Shape
• Image reconstruction
• Solid modeling
• Partial Observation
• Object Database
• 3D Models Of Buildings
• Global Map
• Segmentation Map
• Object Surface
• Object Dataset
• Deep Neural Network
• Object Detection
• Point Cloud
• Depth Map
• Depth Images
• Highest Count
• Mapping System
• Objects In The Scene
• Random Sample Consensus
• Camera Pose
• Laser Ranging
• Object Instances
• Iterative Closest Point
• Surface Normals
• Segmentation Labels
• RGB-D Sensor
• Scene Reconstruction
• Voxel Grid
• Geometric Consistency
• Camera Pose Estimation
• Depth Measurements
• Loop Closure
• Object Recognition