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DVS Image Reconstruction

Cedric Scheerlinck

This repository contains (1) Complementary filter (combines events and frames) and (2) High pass filter (pure event reconstruction). It can be used to reconstruct a continuous-time image representation of the event stream.

filter_pic

This package was developed using ROS version Kinetic (Ubuntu 16.04). It can be run in real-time using (1) live DVS (RPG Event Camera Driver), or (2) pre-recorded rosbag (data, Color Event Dataset).
Got a noisy rosbag? Try the hot pixel filter.
The jupyter notebook demo version is now available.

The source code is released under the MIT License.

Publication

If you use this work in an academic context, please cite the following work (PDF, BibTex):

  • Cedric Scheerlinck, Nick Barnes, Robert Mahony, "Continuous-time Intensity Estimation Using Event Cameras", Asian Conference on Computer Vision (ACCV), Perth, 2018.

Install Instructions

Please replace <YOUR VERSION> with your ROS version (e.g. kinetic).

Install libusb, catkin tools, vcstool and autoreconf:

sudo apt install libusb-1.0-0-dev python-catkin-tools python-vcstool dh-autoreconf

Install ROS dependencies:

sudo apt install ros-<YOUR VERSION>-camera-info-manager ros-<YOUR VERSION>-image-view

Create a new catkin workspace if needed:

mkdir -p ~/catkin_ws/src && cd ~/catkin_ws/
catkin config --init --mkdirs --extend /opt/ros/<YOUR VERSION> --merge-devel --cmake-args -DCMAKE_BUILD_TYPE=Release

Clone this repository:

cd src/
git clone https://github.com/cedric-scheerlinck/dvs_image_reconstruction.git

Clone dependencies:

vcs-import < dvs_image_reconstruction/dependencies.yaml

Add udev rule to run live DVS (see RPG Event Camera Driver):

cd rpg_dvs_ros/libcaer_catkin/
sudo ./install.sh

Build the packages:

catkin build davis_ros_driver complementary_filter pure_event_reconstruction
source ~/catkin_ws/devel/setup.bash

Downloads

Datasets can be found here.
The Color Event Dataset containing color frames and events is now available!

Video

dvs_image_reconstruction_video https://youtu.be/bZ0ZKido0Ag

Website

The webpage for this project with links to data, slides, paper and more can be found here:

https://cedric-scheerlinck.github.io/continuous-time-intensity-estimation

Acknowledgements

This research was funded by an Australian Government Research Training Program Scholarship (AGRTP) and the Autralian Research Council through the Australian Centre of Excellence for Robotic Vision (ACRV) CE140100016.

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Code for "Continuous-time Intensity Estimation Using Event Cameras" (ACCV, 2018)

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