• Artificial Intelligence and Image Processing

• ConfLab: A Data Collection Concept, Dataset, and Benchmark for Machine Analysis of Free-Standing Social Interactions in the Wild

This file contains the annotations for the ConfLab dataset, including actions (speaking status), pose, and F-formations. 

------------------

./actions/speaking_status:

./processed: the processed speaking status files, aggregated into a single data frame per segment. Skipped rows in the raw data (see https://josedvq.github.io/covfee/docs/output for details) have been imputed using the code at:  https://github.com/TUDelft-SPC-Lab/conflab/tree/master/preprocessing/speaking_status

    The processed annotations consist of:

        ./speaking: The first row contains person IDs matching the sensor IDs,

        The rest of the row contains binary speaking status annotations at 60fps for the corresponding 2 min video segment (7200 frames).

        ./confidence: Same as above. These annotations reflect the continuous-valued rating of confidence of the annotators in their speaking annotation.

To load these files with pandas: pd.read_csv(p, index_col=False)

./raw-covfee.zip: the raw outputs from speaking status annotation for each of the eight annotated 2-min video segments. These were were output by the covfee annotation tool (https://github.com/josedvq/covfee)

Annotations were done at 60 fps.

--------------------

./pose:

./coco: the processed pose files in coco JSON format, aggregated into a single data frame per video segment. These files have been generated from the raw files using the code at: https://github.com/TUDelft-SPC-Lab/conflab-keypoints

    To load in Python: f = json.load(open('/path/to/cam2_vid3_seg1_coco.json'))

    The skeleton structure (limbs) is contained within each file in:

        f['categories'][0]['skeleton']

    and keypoint names at:

        f['categories'][0]['keypoints']

./raw-covfee.zip: the raw outputs from continuous pose annotation. These were were output by the covfee annotation tool (https://github.com/josedvq/covfee)

    Annotations were done at 60 fps.

---------------------

./f_formations:

seg 2: 14:00 onwards, for videos of the form x2xxx.MP4 in /video/raw/ for the relevant cameras (2,4,6,8,10). 

seg 3: for videos of the form x3xxx.MP4 in /video/raw/ for the relevant cameras (2,4,6,8,10). 

Note that camera 10 doesn't include meaningful subject information/body parts that are not already covered in camera 8. 

First column: time stamp

Second column: "()" delineates groups, "<>" delineates subjects, cam X indicates the best camera view for which a particular group exists.

phone.csv: time stamp (pertaining to seg3), corresponding group, ID of person using the phone

• 2022-06-07 first online

• 2022-10-10 published, posted

• NWO 639.022.606.
• Aspasia grant associated with vidi grant 639.022.606.

Your request will be sent to the owner of the dataset.