Reality Data Analysis

Context Detectors

The analysis performed by an RDA job usually requires one or more Machine Learning models (e.g. a deep learning neural network). We call them ContextDetectors.

ContextDetectors are specific to RDA and provided by Bentley. They are classified in different categories, each RDA job type requiring a given category. Here are the categories used by current RDA jobs:

  • photo object detector: ML model detecting objects as boxes in a photo.
  • photo segmentation detector: ML model classifying pixels in a photo (semantic segmentation).
  • orthophoto segmentation detector: ML model classifying pixels in an orthophoto (semantic segmentation). The difference with a photo segmentation detector is that pixel resolution is taken into account to improve detection.
  • point cloud segmentation detector: ML model classifying points in a point cloud (semantic segmentation)

ContextDetectors are the basic blocks of RDA: limiting to these categories does not mean that analysis is limited to these basic tasks. For instance, 3D object detection is available but uses either a photo object detector or a point cloud detector underneath. Mesh analysis is also available, etc.

Download available ContextDetectors on the Context Insights detectors download page. This page has been designed for ContextInsights, the on premise version of RDA. To use one of them with RDA, just upload it to RDS in your Enterprise projects.