# Face-Yaw-Roll-Pitch-from-Pose-Estimation-using-OpenCV

**Repository Path**: mirrors_Z-Q-Yang/Face-Yaw-Roll-Pitch-from-Pose-Estimation-using-OpenCV

## Basic Information

- **Project Name**: Face-Yaw-Roll-Pitch-from-Pose-Estimation-using-OpenCV
- **Description**: This work is used for pose estimation(yaw, pitch and roll) by Face landmarks(left eye, right eye, nose, left mouth, right mouth and chin)
- **Primary Language**: Unknown
- **License**: MIT
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2020-09-26
- **Last Updated**: 2026-04-26

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# Face-Yaw-Roll-Pitch-from-Pose-Estimation-using-OpenCV

## Description
This work is used for pose estimation(yaw, pitch and roll) by Face landmarks(left eye, right eye, nose, left mouth, right mouth and chin).
Roll:+90°：-90°/Pitch:+90°：-90°/Yaw:+90°：-90°, like the picture below:

![Roll_Pitch_Yaw.png](https://github.com/jerryhouuu/Face-Yaw-Roll-Pitch-from-Pose-Estimation-using-OpenCV/blob/master/pictures/image001.png?raw=true)

The order of numbers is **ROLL**, **PITCH**, **YAW**： 
![Jay_Result1.png](https://github.com/jerryhouuu/Face-Yaw-Roll-Pitch-from-Pose-Estimation-using-OpenCV/blob/master/pictures/jay.jpg?raw=true)
![Jay_Result2.png](https://github.com/jerryhouuu/Face-Yaw-Roll-Pitch-from-Pose-Estimation-using-OpenCV/blob/master/pictures/jay2.JPEG?raw=true)
![Jay_Result3.png](https://github.com/jerryhouuu/Face-Yaw-Roll-Pitch-from-Pose-Estimation-using-OpenCV/blob/master/pictures/jay3.JPEG?raw=true)

## Preprocessing
* I fine-tune the MTCNN into the output of 6 landmark feature points, reference and make some adjustments in this article 'Head Pose Estimation using OpenCV and Dlib'.
* Because the MTCNN's eyes are the middle of the position rather than the corner of the eye, so we modify the world coordinate(model point) from original to (-150.0, -150.0, -125.0)# Left Mouth corner/(150.0, -150.0, -125.0)# Right mouth corner
* Modify the camera matrix's focal_length from original to img_size[1]/2 / np.tan(60/2 * np.pi / 180).

## Step
1. imgpts, jac = cv2.projectPoints(axis, rotation_vector, translation_vector, camera_matrix, dist_coeffs)
2. modelpts, jac2 = cv2.projectPoints(model_points, rotation_vector, translation_vector, camera_matrix, dist_coeffs)
3. rvec_matrix = cv2.Rodrigues(rotation_vector)[0]
4. proj_matrix = np.hstack((rvec_matrix, translation_vector))
5. eulerAngles = cv2.decomposeProjectionMatrix(proj_matrix)[6] 
6. pitch, yaw, roll = [math.radians(_) for _ in eulerAngles]
7. pitch = math.degrees(math.asin(math.sin(pitch)))
8. roll = -math.degrees(math.asin(math.sin(roll)))
9. yaw = math.degrees(math.asin(math.sin(yaw)))

## References
1. [Head Pose Estimation using OpenCV and Dlib](https://www.learnopencv.com/head-pose-estimation-using-opencv-and-dlib/)
2. [MTCNN-tensorflow](https://github.com/AITTSMD/MTCNN-Tensorflow)