Living Room Smart Home Gesture Control Dataset
#Gesture Recognition #Action Detection #Human-Computer Interaction Optimization #Smart Home #Gesture Recognition #Human-Computer Interaction #Automation Control
- 500 records
- 1.3G
- MP4
- CC-BY-NC-SA 4.0
MOBIUSI INC
Updated:2026-02-04
AI Analysis & Value Prop
With the development of smart home technology, how to achieve efficient control of devices through simple, natural gestures has become one of the challenges in the industry today. Traditional smart devices rely heavily on voice and physical button control, which have limitations in complex environments or among special groups. The Living Room Smart Home Gesture Control Dataset aims to enhance the recognition accuracy and response speed of smart devices to meet more efficient and diverse user needs. This dataset includes various gesture videos collected in typical home living room environments using HD camera equipment, covering various lighting conditions and background complexities. Quality control is rigorous, involving multiple rounds of annotation and consistency checks, and review by an expert team with a background in computer vision. Data preprocessing steps include video clipping, frame-by-frame processing, and feature annotation, ultimately stored in MP4 format, neatly categorized for quick retrieval.
Dataset Insights
Sample Examples
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| duration | string | Duration |
| quality | string | Resolution |
| gesture_type | string | The type of gesture action in the video, such as 'hand waving' or 'finger tap'. |
| duration_of_gesture | float | The duration of the gesture action in the video, measured in seconds. |
| gesture_start_frame | int | The frame number where the gesture action starts in the video. |
| gesture_end_frame | int | The frame number where the gesture action ends in the video. |
| lighting_conditions | string | The lighting conditions during the video recording, such as 'bright' or 'dim'. |
| background_clutter | string | The level of clutter in the background of the video, such as 'clean' or 'messy'. |
| subject_position | string | The position of the subject performing the gesture in relation to the camera, such as 'close' or 'far'. |
| subject_pose | string | The posture of the subject performing the gesture in the video, such as 'standing' or 'sitting'. |
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 is the Living Room Smart Home Gesture Control Dataset?
- The Living Room Smart Home Gesture Control Dataset is a dataset used for training and improving the gesture recognition capabilities of smart devices, containing video modality data.
- What applications is the Living Room Smart Home Gesture Control Dataset suitable for?
- This dataset is suitable for developing and optimizing gesture recognition systems for smart home devices, enhancing user interaction with devices.
- How can the Living Room Smart Home Gesture Control Dataset improve accuracy?
- By using this dataset to train models, the accuracy of gesture recognition in smart home devices can be improved, making them more precise and efficient.
- What gestures are included in the Living Room Smart Home Gesture Control Dataset?
- The dataset includes a variety of common living room gestures that can be recognized by smart devices and used to control home appliances.
- Why choose video as the data modality?
- The video data modality can capture dynamic changes in gestures, making it more suitable for accurate gesture recognition and control compared to static images.
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Verified for Enterprise UseCite this Work
@dataset{Mobiusi2026,
title={Living Room Smart Home Gesture Control Dataset},
author={MOBIUSI INC},
year={2026},
url={https://www.mobiusi.com/datasets/44622f87f32dd77c966e3def52140843},
urldate={2026-02-04},
keywords={Smart home gesture dataset, video gesture control, human-computer interaction data, living room gesture recognition},
version={1.0}
}Using this in research? Please cite us.
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