rgb-d based people detection, tracking and prediction.
this is build to run on Ubuntu 18 with ROS melodic.
to run on ROS kinetic/Ubuntu 16 edits would need to be made to the build files, particularly how the eigen library is imported.
go to hyperion/hyperion
data and run sh get_data.sh
. you will need to have p7zip
installed (sudo apt install p7zip
) to unzip the data file.
everything builds with catkin_make
start ros: roscore
start publishing people tracks by running rosrun hyperion_detect hyperion_detect_node
run a 30 second data collection and analysis with rosrun hyperion_predict hyperion_predict_node
.
once the collection has run notes can be added to the file by answering the prompt. once this is done a evaluation file will be created.
there is a evaluation file that gived a detailed output of prediction data and it's acuracy, both on a per trial basis and on average. there is also a number of gnuplot scripts for creating plots of the data.
the model for the python RNN model was created in google colab, the code can be seen here motion_prediction_lstm this model was trained on part of the atc shopping center tracks. and implemented to enhance the KF prediction.