This project is imported from
-Python code: folder:src
1.optical_flow.ipynb
a.definitions of spatial and temporal filters
b. visualization of filters above in 2d or 3d view
c.implementation of equation (Eq 23) in 1[@tschechneBioInspiredOpticFlow2014] and visualization
d.using aggregation to calculate the velocity at each pixel for optical flow based on separable filters and visualization(Eq.33 1)
e. .npy files are the intermediate files
-Dataset:
This is the dataset which is used in this project.For this dataset, only event.txt is used.
One can also find other datasets in here: http://rpg.ifi.uzh.ch/davis_data.html
-Figures:
the generated figures are saved in the folder: output_figures
-Slides:
This is the folder contains the slides which explains some general ideas of this project.
numpy,
matplotlib,
pandas,
opencv (cv2),
- [1] Brosch Tobias, Tschechne Stephan, Neumann Heiko,On event-based optical flow detection
- [2] Tschechne, Stephan and Sailer, Roman and Neumann,Heiko.Bio-Inspired Optic Flow from Event-Based Neuromorphic Sensor Input
- [3]Tschechne, Stephan and Brosch, Tobias and Sailer, Roman and von Egloffstein, Nora and Abdul-Kreem, Luma Issa and Neumann, Heiko.On Event-Based Motion Detection and Integration