What is the best way for frame construction?

What is the best way to convert events(x,y,polarity,time stamp) that are obtained from event camera via ROS to Frames?

[M]

Hi @Image Analyst, Do you have any idea please?

Answer 1

[recent works]

Converting events from an event camera (also known as a dynamic vision sensor, DVS) to traditional frames is a process called event-based frame reconstruction. Event cameras capture changes in pixel intensity as a stream of events, typically consisting of (x, y, polarity, timestamp) data, where (x, y) represents the location of the event, polarity indicates whether the event represents an increase or decrease in intensity, and timestamp records the time when the event occurred. To convert these events into frames, you can use various methods and algorithms.

import numpy as np

import cv2

import rospy

from dvs_msgs.msg import EventArray

# Initialize the frame and time variables

frame_width, frame_height = 640, 480 # Set your desired frame resolution

frames = np.zeros((frame_height, frame_width), dtype=np.uint8)

current_time = 0

# Define a time window for accumulating events (in microseconds)

time_window = 10000 # 10 ms

# Callback function for processing incoming events

def event_callback(event_array):

global frames, current_time

for event in event_array.events:

x, y, polarity, timestamp = event.x, event.y, event.polarity, event.ts.to_nsec()

# Check if the event is within the time window

if timestamp - current_time > time_window:

# Visualize or process the accumulated frame(s) here

cv2.imshow("Reconstructed Frame", frames)

cv2.waitKey(1)

# Reset the frame and current time

frames = np.zeros((frame_height, frame_width), dtype=np.uint8)

current_time = timestamp

# Update the pixel based on event polarity

frames[y, x] = 255 if polarity else 0

if __name__ == "__main__":

rospy.init_node("event_to_frame_converter")

rospy.Subscriber("/dvs/events", EventArray, event_callback)

rospy.spin()

This code listens to ROS messages containing events and accumulates them into frames within a specified time window. When the time window is exceeded, it displays the accumulated frame(s) and resets for the next accumulation. You'll need to adapt it to your specific event camera and ROS setup

[M]

@recent works Thanks but do you have MATLAB code because I imorted the events in MATLAB? Also is there a way other than accumulating the events and can be used for real time applications?

To convert these events into frames, you can use various methods and algorithms.

Do you know if there is a Matlab representation for these methods? and what do you think the best way can be used for real-time?

[recent works]

% Initialize variables

frame_width = 640; % Set your desired frame resolution

frame_height = 480;

frames = zeros(frame_height, frame_width, 'uint8');

% Set a time window for visualization (in microseconds)

time_window = 10000; % 10 ms

% Create a figure for real-time display

figure;

h = imshow(frames);

% Loop through your event data (replace with your actual event data)

for i = 1:numel(events)

event = events(i);

x = event.x;

y = event.y;

polarity = event.polarity;

timestamp = event.timestamp; % Timestamp in microseconds

% Check if the event is within the time window

if timestamp - current_time > time_window

% Display the accumulated frame

set(h, 'CData', frames);

drawnow;

% Reset the frame and current time

frames = zeros(frame_height, frame_width, 'uint8');

current_time = timestamp;

end

% Update the pixel based on event polarity

if polarity

frames(y, x) = 255;

end

end

[M]

@recent works Thanks, do you have an idea how to reduce the noise because my camera is noisy (DVD mini plorer) and I couldn't find fast way to reduce the noise, especially for online processing?

[M]

@recent works Do you know how to store the images as matrices not as image in your code?

[recent works]

% Initialize variables

frame_width = 640; % Set your desired frame resolution

frame_height = 480;

frames = zeros(frame_height, frame_width, 'uint8');

% Set a time window for visualization (in microseconds)

time_window = 10000; % 10 ms

% Create a cell array to store frames as matrices

frame_cell = cell(1);

% Loop through your event data (replace with your actual event data)

for i = 1:numel(events)

event = events(i);

x = event.x;

y = event.y;

polarity = event.polarity;

timestamp = event.timestamp; % Timestamp in microseconds

% Check if the event is within the time window

if timestamp - current_time > time_window

% Store the accumulated frame as a matrix

frame_cell{end+1} = frames;

% Reset the frame and current time

frames = zeros(frame_height, frame_width, 'uint8');

current_time = timestamp;

end

% Update the pixel based on event polarity

if polarity

frames(y, x) = 255;

end

end

% Now, frame_cell contains frames as matrices

[M]

@recent works what is current_time ?

I have x y polarity timestamp as matrices

[M]

@recent works I didnt get these lines

if timestamp - current_time > time_window

current_time = timestamp;

% Update the pixel based on event polarity

if polarity

frames(y, x) = 255;

end

please elaborate