Without any order of importance, I hereby acknowledge the great work done by all the developers Involved in the implementation of each one of the packages that I used in my thesis and my thank you for sharing the code that enables me to implement a new aplication. Without the work made by this developers I would be in grave trouble.
"Standing on the shoulders of giants" - Bernard of Chartres
To cite the work use:
A. Silva, R. Mendonça and P. Santana. Monocular Trail Detection and Tracking Aided by Visual SLAM for Small Unmanned Aerial Vehicles. Journal of Intelligent & Robotic Systems (in press), DOI: 10.1007/s10846-019-01033-x, 2019.
The article can be found here
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LSD-SLAM Package. Please refer to: (Official repo) https://github.com/tum-vision/lsd_slam (Official page) http://vision.in.tum.de/research/vslam/lsdslam?redirect=1
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Video Stream Opencv Package. Please refer to: (Official repo) https://github.com/ros-drivers/video_stream_opencv (ROS page) http://wiki.ros.org/video_stream_opencv
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P. Santana, R. Mendonça, L. Correia and J. Barata. Neural-Swarm Visual Saliency for Path Following. Applied Soft Computing, Vol. 13, No. 6, pp. 3021- 3032, 2013 (Paper) http://home.iscte-iul.pt/~pfsao/papers/asc_2012.pdf
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Image Proc Package. Please refer to: (Official repo) https://github.com/ros-perception/image_pipeline (ROS page) http://wiki.ros.org/image_proc
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G2O Framework . Please refer to: (Official repo) https://github.com/RainerKuemmerle/g2o (Official Page) http://openslam.org/g2o.html
Part of my work needs some additional features added to the LSD-SLAM code, all the modifications are hereby commited and available to all, but the core of the algorithm has not changed in any way.
This work it's not suitible for real world usage, so i'm not responsible in any way or form for the usage of this code in real world applications, this code is intended to be used in a controled enviroment.