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Learnable Camera Motion Models


This project started January 2015.
The project runs for four years, and is funded by The Swedish Research Council (VR).

New: We are offering a masters thesis project on Machine Learning for Camera Based Trail Mapping. We have previously done video stabilization under difficult cases, see e.g. this video, and are now extending this to a full structure-from-motion system, that will handle video from e.g. a MTB mounted camera. The project involves 3D geometry, machine learning and opportunities for attending a scientific conference. Contact us for details.

People

The principal investigator for this project is Per-Erik Forssén.
The project also employs the PhD student Hannes Ovrén.

Research Topic

In this project, we develop continuous camera motion models that can be adapted to specific situations through learning. Such models are needed in video stabilisation and rectification on mobile platforms. They are also useful for control of motorised gimbals that mechanically stabilise the camera aim.

The project is a continuation of the VGS project.

Datasets

Publications


Senast uppdaterad: 2017-10-23