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Human Activity Recognition Dataset – 2,341 People, 11 Actions in Online Conference Scenes

human action recognition dataset
human activity recognition dataset
human pose dataset
gesture recognition dataset
human behavior dataset

This dataset collected from 2,341 people in online conference scenarios. Participants includes Asians, Caucasians, blacks, and browns. The age is mainly young and middle-aged. It collects a variety of indoor office scenes, covering meeting rooms, coffee shops, libraries, bedrooms, etc. Each person collected 11 videos, including human body behaviors such as shaking the body from side to side, eating, and stretching. This dataset can be applied to tasks including human activity recognition, human action recognition, human behavior analysis, human pose estimation, and gesture recognition.

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SpecificationsSpecifications
Data size
2,341 people, each person collects 11 videos
Race distribution
786 Asians, 1,002 Caucasians, 401 black, 152 brown people
Gender distribution
1,210 males, 1,131 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 human behaviors, 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
Accuracy rate
the accuracy exceeds 97% based on the accuracy of the actions; the accuracy of action naming is more than 97%
Sample Sample
  • Human Activity Recognition Dataset – 2,341 People, 11 Actions in Online Conference Scenes
  • Human Activity Recognition Dataset – 2,341 People, 11 Actions in Online Conference Scenes
  • Human Activity Recognition Dataset – 2,341 People, 11 Actions in Online Conference Scenes
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