Public Lab Research note

Palantier: impressive image stitching for UAVs and kites

by warren | February 05, 2012 17:11 | 429 views | 5 comments | #749 | 429 views | 5 comments | #749 05 Feb 17:11

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Mark Willis sez:

Palentier is an Open Source software that was originally created by me and a good friend (M. Stange) for processing aerial images from un-manned aerial vehicles (UAVs) like the MikroKopter. Palentier can process aerial photographs into georeferenced and scaled images which accurately reflect the location and size of objects in the real world. These images can be exported to Google Earth or to GIS software, like ArcGIS, for review and analysis.

Our current attempt is to modify the software so that it could be useable by the KAP community. Several weeks ago, I asked for help with test images and rig GPS data from fellow KAPers. You came through and we now have results from using Palentier with KAP imagery. The system was tested using data from four places (Northern England, and Northern Libya, Southern Texas, and West Virginia). All had good results and all but one (West Virginia which I don't have permission to share publicly) are shown here.

More on the Palentier software:

(from the FreeMapStudio2012 wiki page:


really like this. is there any way to integrate the system they use to reproject using GPS data into MapKnitter?

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Did anything ever come of this? I've been searching for open source UAV-mapping apps and I came across Palentier. Unfortunately, it doesn't look like much has been going on in the past two years.

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I'm not really sure! Maybe @patcoyle has an idea of the state of the art in 3d mapmaking?

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One of my research notes had a discussion about 3D Mapmaking in comment thread. I was asking if anyone had ever heard of using OpenCV for orthorectification in 3D mapping and the closest I could find online was this short lived discussion on stackexchange. Also, @mathew created this post back in February-

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This looks interesting-

 MAP-Tk is an open source C++ collection of libraries and tools for making measurements from aerial video. Initial capability focuses on estimating the camera flight trajectory and a sparse 3D point cloud of the scene. These products are jointly optimized via sparse bundle adjustment and are geo-localized if given additional control points or GPS metadata.
 This project has similar goals as projects like Bundler and VisualSFM. However, the focus here in on efficiently processing aerial video rather than community photo collections. Special attention has been given to the case where the variation in depth of the 3D scene is small compared to distance to the camera. In these cases, planar homographies can be used to assist feature tracking, stabilize the video, and aid in solving loop closure problems.
 The MAP-Tk software architecture is highly modular and provides an algorithm abstraction layer that allows seamless interchange and run-time selection of algorithms from various other open source projects like OpenCV, VXL, VisCL, and PROJ4. The core library is light-weight with minimal dependencies (C++ standard library plus some Boost components). The tools are written to depend only on the MAP-Tk core library. Additional capabilites are provided in add-on modules that use 3rd party libraries to implement various abstract algorithm interfaces defined in the core.
 While the initial software implementation relies on batch post-processing of aerial video. Our intent is to move to an online video stream processing framework and optimize the algorithms to real-time performance for use onboard unmanned aerial vehicles.

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