eye-contact-cnn

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eye-contact-cnn

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This project uses AI to detect and correct eye contact in real-time video or images. It leverages computer vision and deep learning models to adjust gaze direction, making it appear as if the subject is maintaining eye contact with the camera.

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Correcting gaze by warping-based convolutional neural network.

# System usage
```python
python regz_socket_MP_FD.py
```

# Parameters need to be personalized in the "config.py"
The positions of all parameters are illustrated in the following figure. P_o is the original point (0,0,0) which is defined at the center of the screen. 
 
Parameters "P_c_x", "P_c_y", "P_c_z", "S_W", "S_H", and "f" need to be personalized before using the system. 
"P_c_x", "P_c_y", and "P_c_z": relative distance between the camera position and screen center (cm) 
"S_W" and "S_H": screen size (cm) 
"f": focal length of camera

# Calibrating the focal length of the camera by the attached tools
Execute the script "focal_length_calibration.ipynb" or "focal_length_calibration.py" to estimated the focal length (f), and the value will be shown at the top-left corner of the window. 
Steps for calibration: 
Step 1, please place your head in front of the camera about 50 cm (you can change this value in the code) 
Step 2, please insert your interpupillary distance (the distance between two eyes) in the code or use the average value, 6.3 cm

# Starting to correct gaze! (Self-demo)
Push 'r' key when focusing the "local" window and gaze your head on the "remote" window to start gaze correction. 
Push 'q' key when focusing the "local" window to leave the program. 
 
*The video will delay at beginning because the TCP socket transmission, nevertheless, the video will be on time after few seconds.

# For online video communication
The codes at the local and remote sides are the same. However, parameters "tar_ip", "sender_port", and "recver_port" need to be defined at both sides. 
"tar_ip": the other user's IP address 
"sender_port": port # for sending the redirected gaze video to the other user 
"sender_port": port # for getting the redirected gaze video from the other user

# IP setup for self-demo
The codes at the local and remote sides are the same. However, parameters "tar_ip", "sender_port", and "recver_port" need to be defined at both sides. 
"tar_ip": 127.0.0.1 
"sender_port": 5005 
"sender_port": 5005

# Environmental setup
Python 3.5.3 
Tensorflow 1.8.0 
Cuda V9.0.176 and corresponding cuDnn

# Required packages
Dlib 18.17.100 
OpenCV 3.4.1 
Numpy 1.15.4 + mkl 
pypiwin32 
scipy 0.19.1

# DIRL Gaze Dataset
37 Asian volunteers participated in our dataset collection. About 100 gaze directions are collected in range +40 to -40 degrees in horizontal and +30 to -30 degrees in vertical, in which 63 and 37 images are fixed and random direction, respectively. The images with closed eyes were removed.

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