Auditorium Host Posture Estimation Dataset
#posture estimation #action recognition #video analysis #intelligent security #human-computer interaction #virtual reality #sports analysis
- 500 records
- 1.6G
- MP4
- CC-BY-NC-SA 4.0
MOBIUSI INC
Updated:2026-02-04
AI Analysis & Value Prop
In the fields of modern intelligent security and human-computer interaction, posture recognition technology faces challenges such as handling complex actions, occlusions, and lighting variations. Existing solutions have limited performance when processing large-scale video data and insufficient accuracy in recognizing diverse actions. This dataset is dedicated to solving the challenges of posture estimation in multi-role, multi-view, and complex environments, meeting the needs of intelligent security and virtual reality response services. Data is collected using high-definition camera equipment in various environments, including auditoriums, conference rooms, and outdoor activities. Quality control measures such as multiple rounds of annotation, multi-point video synchronization quality checks, and expert reviews are implemented. The annotation team consists of 20 people with backgrounds in computer vision. Data preprocessing includes background modeling, lighting balancing, and posture feature extraction, stored in segmented MP4 format with structured metadata in JSON files for indexing.
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| duration | string | Duration |
| quality | string | Resolution |
| pose_keypoints | json | The coordinates of the presenter's body pose keypoints in the video. |
| action_labels | string | Labels for specific actions performed by the presenter in the video. |
| background_description | text | Description of the background environment in the video. |
| expression | string | Description of the presenter's expression in the video. |
| camera_angle | string | Information about the camera angle while shooting the video. |
| lighting_conditions | string | The lighting conditions during the video shooting. |
| clothing_description | text | Description of the clothing worn by the presenter in the video. |
| emotional_tone | string | The overall emotional tone conveyed by the presenter in the video. |
| gesture_intensity | string | The intensity of gestures made by the presenter in the video. |
| audience_interaction | string | Information regarding the presenter's interaction with the audience in the video. |
Compliance Statement
| Authorization Type | CC-BY-NC-SA 4.0 (Attribution–NonCommercial–ShareAlike) |
| Commercial Use | Requires exclusive subscription or authorization contract (monthly or per-invocation charging) |
| Privacy and Anonymization | No PII, no real company names, simulated scenarios follow industry standards |
| Compliance System | Compliant with China's Data Security Law / EU GDPR / supports enterprise data access logs |
Frequently Asked Questions
- What application scenarios are suitable for the Auditorium Presenter Pose Estimation Dataset?
- This dataset is suitable for auditorium performance analysis, pose recognition research, and machine learning training applications.
- What type of video data is included in the Auditorium Presenter Pose Estimation Dataset?
- The dataset includes videos of auditorium presenters for training and testing pose recognition.
- How can the Auditorium Presenter Pose Estimation Dataset be used to improve pose recognition accuracy?
- By deeply analyzing patterns of pose changes in presenter videos, researchers can enhance algorithm accuracy and robustness in recognizing different poses.
- Why choose the Auditorium Presenter Pose Estimation Dataset for pose recognition research?
- Reasons for choosing this dataset include its diversity in specific scenarios and rich pose variations, which help in developing more generalized pose recognition algorithms.
- What distinguishes the Auditorium Presenter Pose Estimation Dataset from other pose recognition datasets?
- This dataset focuses on presenter poses in auditorium settings, while other datasets may focus on pose recognition tasks in various other scenes or environments.
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Verified for Enterprise UseCite this Work
@dataset{Mobiusi2026,
title={Auditorium Host Posture Estimation Dataset},
author={MOBIUSI INC},
year={2026},
url={https://www.mobiusi.com/datasets/13d3a06448300ebb6125926d360518fb?dataset_scene_id=16},
urldate={2026-02-04},
keywords={posture estimation dataset, action recognition video, intelligent security video, posture recognition},
version={1.0}
}Using this in research? Please cite us.
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