Roadmap

Short Term

• Expose GDAL creation options to command line:
  • compression
  • tiling
  • target srs
  • bigtiff
• Improve georeferencing / coordinate system throughout entire pipeline
  • Needs to be an integrated part of the the pipeline, not a single process at the end
  • Feature branch:
• Improve Object Oriented Codebase
• Implement Testing Framework.
• Video/SLAM reconstruction
  • PR #317
• Update Dependencies
  • pyexiv2 vs. gexiv2
  • vtk6 (Ubuntu 16.10)
• Add optional pre-calibration tool, maybe with editable library of lens parameters derived from checkerboard calibration process
  • Formalization of Pau, Dakota, and other’s work
  • add link in new documentation for dockerized version
  • Optimization of processing when using corrected imagery
• GCP positioning input alternatives
  • Web Interface for creating GCP
• Add TIFF / Multispec support

Medium Term Improvements

• Point cloud partitioning / classification
  • Progressive morphological filter via PDAL
    • http://www.pdal.io/stages/filters.ground.html
    • Status:
      • No current work, but simple addition of PDAL functionality. Need build process which allows for necessary dependencies
    • Advantage: Allows for classification of ground point cloud for partitioning of mesh creation / quality, hydrological applications, etc.
    • Classifications based on machine learning of input raw images
• Improvement of meshing (treat buildings differently than vegetation than ground, etc.)
• Change meshing from Poisson to alternate mesh (not water tight?)
  • Use different mesh approaches based on classification of data
  • Identification of flat surfaces
    • e.g. http://blog.spotscale.com/2016/03/29/make-it-flat/
  • 3D / 2D Breaklines
    • Specialized interface or iD
    • OSM or custom
    • Possibly integrate with OSM workflow and iterate orthos
    • Alternatively digitize directly on raw images
• DEM generation, see and integrate:
  • https://smathermather.com/2016/10/21/filtering-buildings-and-vegetation-from-drone-derived-surface-models/
  • https://smathermather.com/2016/10/15/finding-peace-finding-the-grounddrone-flights-for-hydrologic-modeling/
  • Dependency for PDAL
• Web
  • Development of Python node API — node-OpenDroneMap
    • https://github.com/pierotofy/node-OpenDroneMap
  • Development of web front end(s) — WebODM
    • https://github.com/opendronemap/WebODM
    • https://github.com/AmericanRedCross/posm
• Integration with OpenAerialMap
• Orthophoto improvements
  • Crop tiff output to high probability good data (convex or concave hull) by default (flag to output all)
• Development of an API

Long Term

• Shift from toolchain to 'toolbox' approach
  • See proposal
• Texturing
  • Add vignetting correction to toolchain
  • BRDF?
  • Fix interpolation gradients (CIR use case)
    • Document fix (disable tag)
• Error Calculations and reporting
• Logging: Progress Status
  • Markers in log for process for rubber sheeting to state
  • Image Matching refinement of progress
• Optimization
  • GPU
  • Incremental SfM
  • Clusterability
    • Possibilities:
      • Shared file system + celery workers
      • Smarter approach using data localization
      • PySpark
        • Working in terms of data frames
        • Lambda expressions that can be sent out to separate machines
        • Process steps need to be more granular
      • Serializable intermediate representation
  • Chunking
• Find automated rubber sheeting solution for rubber sheeting to other datasets

Ideas

• NDVI
• Atmospheric correction
• Automatic GCP Extraction
• Manned aircraft app
• Single tiled aerial of OAM outputs
• Fly around house and create model
  • Image Masking
  • (mapillary semantic segmentation)
• Streetview
• Flight Planning app