We are a part of the Intelligent Robotics Group and we focus on advanced computer vision techniques for planetary mapping, planetary geospatial data, and research aspects of photogrammetry and stereogrammetry.
Lunar Mapping and Modeling
Project Lead: Ara Nefian
NASA’s goal of returning humans to the Moon has led to renewed interest in lunar data sets and lunar science. Our work involves processing on an unprecedented scale, using terabytes of data acquired by the Lunar Reconnaissance Orbiter and newly processed Apollo camera images.
Project Lead: Mike Lundy
The NASA Vision Workbench (VW) is an open-source C++ framework for efficient computer vision. Vision Workbench has been used to create gigapixel panoramas, 3D terrain models from satellite images, and high-dynamic range images for visual inspection.
Project Lead: Ted Scharff
The Neo-Geography Toolkit (NGT) is a suite of automated processing tools
for geospatial data. NGT can transform raster/vector data, metadata and
geo-tagged data into a variety of formats including KML and WTML. NGT is highly
scalable and can process multi-terabyte data sets. NGT was used to help create
WorldWideTelescope | Mars.
Project Lead: Ross Beyer
The Planetary Content project makes NASA's vast stores of planetary data more accessible and useful through Web-enabled tools. In collaboration with Google and other NASA centers, Planetary Content has produced The Moon in Google Earth,
Google Mars 3D, Google Moon (2D maps), and the NASA Gallery in Google Earth. Read about the Google-NASA partnership.
Planetary Data Mining
Project Lead: Ara Nefian
The Content based Planetary Data Mining project offers a web service for planetary image search using both
visual features and metadata information.
Stereo Pipeline
Project Lead: Zachary Moratto
Ames Stereo Pipeline is an open source library for generation and mosaicking of high-quality topographic models from stereo images.
http://ti.arc.nasa.gov/tech/asr/intelligent-robotics/ngt/stereo/
Terrain Reconstruction
Project Lead: Ara Nefian
Digital terrain models have long been essential for science analysis, mission planning and mission operations. We have developed advanced statistical techniques for sub-pixel disparity computation, and image and topography mosaicking. Current research includes albedo reconstruction, photoclinometric terrain reconstruction and Lidar and image co-registration.