DynSLAM
Master's Thesis on Simultaneous Localization and Mapping in dynamic environments. Separately reconstructs both the static environment and the dynamic objects from it, such as cars.
Reconstruct both static and moving objects in real-time from video input for mapping environments.
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DynSLAM has 576 stars on GitHub. It has been forked 178 times. DynSLAM is written mainly in Jupyter Notebook. It has been in active development since 2017. DynSLAM is available under the BSD-3-Clause license. Its main topics are autonomous-vehicles, computer-vision, deep-learning, dense.
What is DynSLAM?
Master's Thesis on Simultaneous Localization and Mapping in dynamic environments. Separately reconstructs both the static environment and the dynamic objects from it, such as cars.
Is DynSLAM open source?
DynSLAM is an open-source project. It is released under the BSD-3-Clause license.
Is DynSLAM free?
Yes. DynSLAM is free and open source — you can use, modify and self-host it.
What license does DynSLAM use?
DynSLAM is available under the BSD-3-Clause license.
What language is DynSLAM written in?
DynSLAM is written mainly in Jupyter Notebook.
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