A unified representation for application of architectural constraints in large-scale mapping

This paper is about discovering and leveraging architectural constraints in large scale 3D reconstructions using laser. Our contribution is to offer a formulation of the problem which naturally and in a unified way, captures the variety of architectural constraints that can be discovered and applied in urban reconstructions. We focus in particular on the case of survey construction with a push broom laser + VO system. Here visual odometry is combined with vertical 2D scans to create a 3D picture of the environment. A key characteristic here is that the sensors pass/sweep swiftly through the environment such that elements of the scene are seen only briefly by cameras and scanned just once by the laser. These qualities make for a an ill-constrained optimisation problem which is greatly aided if architectural constraints can be discovered and appropriately applied. We demonstrate our approach in an end-to-end implementation which discovers salient architectural constraints and rejects false loop closures before invoking an optimisation to return a 3D model of the workspace. We evaluate the precision of this model by comparison to a ground truth provided by a 3rd party professional survey using highend (static) 3D laser scanners

A unified representation for application of architectural constraints in large-scale mapping

This paper is about discovering and leveraging architectural constraints in large scale 3D reconstructions using laser. Our contribution is to offer a formulation of the problem which naturally and in a unified way, captures the variety of architectural constraints that can be discovered and applied in urban reconstructions. We focus in particular on the case of survey construction with a push broom laser + VO system. Here visual odometry is combined with vertical 2D scans to create a 3D picture of the environment. A key characteristic here is that the sensors pass/sweep swiftly through the environment such that elements of the scene are seen only briefly by cameras and scanned just once by the laser. These qualities make for a an ill-constrained optimisation problem which is greatly aided if architectural constraints can be discovered and appropriately applied. We demonstrate our approach in an end-to-end implementation which discovers salient architectural constraints and rejects false loop closures before invoking an optimisation to return a 3D model of the workspace. We evaluate the precision of this model by comparison to a ground truth provided by a 3rd party professional survey using highend (static) 3D laser scanners