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Home > All Category Datasets > Computer Vision Datasets > Human Activity Recognition Dataset – 2,341 People, 23 Actions, Online Conference Scenes

Human Activity Recognition Dataset – 2,341 People, 23 Actions, Online Conference Scenes

human action recognition dataset

human activity recognition dataset

human pose dataset

gesture recognition dataset

mask detection dataset

This dataset collected from 2,341 people in online conference scenarios, Participants include Asian, Caucasian, Black, Brown individuals, mainly young and middle-aged people. Data was collected from a variety of indoor office scenes, covering meeting rooms, coffee shops, library, bedroom, etc. Each participant contributed 23 videos covering actions like opening the mouth, turning the head, closing the eyes, and touching the ears, with 4 images featuring variations such as wearing a mask and sunglasses.This dataset is suitable for tasks such as human activity recognition, human action recognition, human pose estimation, gesture recognition, mask detection, and AI applications in video conferencing and virtual meetings.

This is a paid datasets for commercial use, research purpose and more. Licensed ready made datasets help jump-start AI projects.

Specifications

Specifications

Data size

2,341 people, each person collects 23 videos and 4 images

Race distribution

786 Asians, 1,002 Caucasians, 401 black, 152 brown people

Gender distribution

1,208 males, 1,133 females

Age distribution

from teenagers to the elderly, mainly young and middle-aged

Collection environment

indoor office scenes, such as meeting rooms, coffee shops, libraries, bedrooms, etc.

Collection diversity

different facial multi-pose, different races, different age groups, different meeting scenes

Collection equipment

cellphone, using the cellphone to simulate the perspective of laptop camera in online conference scenes

Collection content

collecting the human behavior data in online conference scenes

Data format

.mp4, .mov, .jpg

Accuracy rate

the accuracy exceeds 97% based on the accuracy of the actions; the accuracy of action naming is more than 97%

Sample

Sample

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