README.md

@@ -1,11 +1,3 @@
 # heatrateestimation
 
-This file contains our work of the heart rate estimation of a person from a video.
-
-## Python
-
-The python will deal with the image extraction and will have to be run each time for new videos.
-
-## Octave
-
-The octave file will work on the bulk of the project to process the data.
+This file contains our work of the heart rate estimation of a person from a video.

frame_extraction.py

@@ -1,3 +1,4 @@
+############
 # frame extraction
 # 
 # Task:
@@ -15,21 +16,4 @@
 # Author: Thomas Périn
 # Date: 17/02/2023
 #
-# Note: check video name when extracting a new one
 ############
-
-import cv2
-
-#Select video by name
-vidcap = cv2.VideoCapture('face_video.mp4')
-success,image = vidcap.read()
-
-#Counter to number the images
-count = 0
-
-#Extraction loop for all images
-while success:
-	cv2.imwrite("img%d.png" % count, image)     # save frame as JPEG file      
-	success,image = vidcap.read()
-	print('Read a new frame: ', success)
-	count += 1

heartRateEstimation.m

@@ -1,51 +1,53 @@
 %hr = heartRateEstimation(imgDirectory, fps, windowDuration, windowShift)
 %%%%%%%%%%%%%%%%%
 % hr = heartRateEstimation(imgDirectory, fps, windowDuration, windowShift)
-%
-% Task: Finding the heartrate of person from selcted images
+% 
+% Task:
 %
 % Inputs:
 %	-imgDirectory
-% -fps
+% 	-fps
+%	-windowDuration
+%	-windowShift
 %
 % Output:
-%	-heartrate:
+%	-hr:
 %
-% Author: Thomas Périn
-% Date: 17/02/2023
+% Author: Guillaume Gibert
+% Date: 06/02/2023
 %
 % Note: images were extracted with ffmpeg -i "video.mkv" ../img/gg_%04d.png
 %%%%%%%%%%%%%%%%%
 
-clc
-clear all
-
-% temp var
-fps = 15;
+%temp var
+imgDirectory = 'img';
+fps = 60;
 windowDuration = 30;
-roi = [280 580 600 850];
+windowShift = 1;
+roi = [225 750 825 1100];
 
-% global
+% global 
 redChannel = [];
 greenChannel = [];
 blueChannel = [];
 
-%list the images with i the same directory
-listImg = dir(['*.png']);
+%list the images
+listImg = dir([imgDirectory '/*.png']);
 
-% iteration for every images available
 for l_img=1:windowDuration*fps
 	% load the current image
-  image_original = imread([listImg(l_img).name]);
-
+	image_original = imread([imgDirectory '/' listImg(l_img).name]);
+	%image(image_original);
+	
 	% crop the current image around the face
 	image_face = image_original(roi(1):roi(2), roi(3):roi(4), :);
-
+	%image(image_face);
+	
 	% spatial average for r, g, b channels
 	r_mean = mean(mean(image_face(:,:,1)));
 	g_mean = mean(mean(image_face(:,:,2)));
 	b_mean = mean(mean(image_face(:,:,3)));
-
+	
 	% store the current "average" pixel in global arrays
 	redChannel = [redChannel r_mean];
 	greenChannel = [greenChannel g_mean];
@@ -53,39 +55,26 @@ for l_img=1:windowDuration*fps
 end
 
 % estimate temporal average and standard deviation
-redChannel_avg = mean(redChannel);
-redChannel_std = std(redChannel);
 greenChannel_avg = mean(greenChannel);
 greenChannel_std = std(greenChannel);
-blueChannel_avg = mean(blueChannel);
-blueChannel_std = std(blueChannel);
 
-% normalize your data
-% first define length of our data
-L = columns(greenChannel);
-for i=1:L
-  greenChannel_normalized(i) = (greenChannel(i) - greenChannel_avg)/greenChannel_std;
-end
+% normalize your data 
+% greenChannel_normalized(i) = (greenChannel(i) - greenChannel_avg)/greenChannel_std
 
-% select only greenChannel for simplicity (no ICA)
-greenChannel_fft = fft(greenChannel_normalized);
+% fft(greenChannel_normalized)
 
-% power spectrum using link(https://www.mathworks.com/help/matlab/ref/fft.html)
-P2 = abs(greenChannel_fft/L);
-P1 = P2(1:L/2+1);
-P1(2:end-1) = 2*P1(2:end-1);
-f = 15*(0:(L/2))/L;
-plot(f,P1)
+% power spectrum (https://www.mathworks.com/help/matlab/ref/fft.html)
 
 % find the peak in the range ([0.75 4] Hz)
-% define range and round to get intergers
-low_index = round(0.75*L/15);
-high_index = round(2*L/15);
-% find max value and index inn new range
-[a, ia] = max(P1(low_index:high_index));
-% adapt the index for full range
-heart_frequency = f(ia+low_index)
+% max -> value, index
+
+% convert the index from Hz to bpm
 
 % determine heart rate
-% convert the index from Hz to bpm
-heart_rate = heart_frequency*60
+
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