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license: cc-by-sa-4.0
tags:
- Engagement
---
# CMOSE: Comprehensive Multi-Modality Online Student Engagement Dataset with High-Quality Labels
## Project page is [here](https://jasonwuchi.github.io/CMOSE/)
## Video clip name
Each video clip is named as videoX_Y_personZ, which means it is the Yth clip of the Zth subject from coaching session X.
## Openface
We extract the second level features from [OpenFace](https://github.com/TadasBaltrusaitis/OpenFace/wiki/Unix-Installation). The extracted files are stored under "secondfeature/videoX_Y_personZ.csv". These features include:
- **Gaze Direction and Angles**
- Three coordinates to describe the gaze direction of left and right eyes respectively
- Two scalars to describe the horizontal and vertical gaze angles
- **Head Position**
- Three coordinates to describe the location of the head relative to the camera
- **Head Rotation**
- Rotation of the head described with pitch, yaw, and roll
- **Facial Action Units (AUs)**
- Intensities of 17 AUs represented as scalars
- Presence of 18 AUs represented as scalars
## I3D
We use the [I3D Repository](https://github.com/v-iashin/video_features) to extract the I3D vectors. One I3D vector is extracted for each clip. The features are stored in "final_data_1.json".
## Acoustics
We use [ParselMouth](https://github.com/YannickJadoul/Parselmouth) to extract the acoustics features. They are stored in "label_results_w_audio_final.json". We also calculate the high level features such as the percentage of high/low volume, high/low pitch, and std of volume/pitch. These are stored in "new_bert_ac_dict.json".
## Narrations
We collect the narrations from the Live Transcript functions in Zoom. They are stored in "label_results_w_audio_final.json". We also extract the bert features from the narrations and store them in "new_bert_ac_dict.json".
## Data split
Split information can be found in "final_data_1.json". Note that "split" should be one of "train", "unlabel", and "test". We use "unlabel" for validation purposes. |