Motion Trajectory Video Tracking Dataset
#object detection #video tracking #action recognition #video analysis #motion detection #content creation
- 500 records
- 1.2G
- MP4
- CC-BY-NC-SA 4.0
MOBIUSI INC
Updated:2026-02-04
AI Analysis & Value Prop
In the current media content industry, video analysis faces increasingly complex challenges, including precise motion tracking and real-time analysis requirements. Traditional video analysis solutions often perform poorly when dealing with complex movements and irregular trajectories, leading to deficiencies in accuracy and efficiency. This dataset focuses on solving the bottlenecks of motion tracking algorithms in terms of accuracy and real-time processing capabilities, meeting the technical needs of diverse video content creation. The dataset is recorded using high-frame-rate cameras in various motion scenarios to ensure diversity and realism of the data. Quality control is ensured through multiple rounds of annotation and expert consistency review, with an annotation team comprising video analysis experts and motion data scientists numbering more than 30 people. Data preprocessing involves steps like noise filtering and image enhancement, with data stored in MP4 format, organized in directories for easy retrieval.
Dataset Insights
Sample Examples
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| duration | string | Duration |
| quality | string | Resolution |
| frame_rate | float | The number of frames displayed per second in the video. |
| codec | string | The encoding format used by the video file. |
| bit_rate | int | The number of bits transferred per second, indicating the quality of the video. |
| video_duration | float | The total playback duration of the video file, measured in seconds. |
| key_frame_interval | int | The number of frames between key frames in the video. |
| aspect_ratio | string | The ratio of width to height of the video. |
| video_format | string | The format of the video file, such as mp4, avi. |
| color_depth | int | The number of bits of color information per pixel. |
| track_object_count | int | The number of moving objects detected in the video. |
| motion_intensity | string | The intensity level of motion in the video, typically categorized as low, medium, high. |
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
- Which sports are suitable for the Motion Trajectory Video Tracking Dataset?
- The Motion Trajectory Video Tracking Dataset is suitable for various sports such as football, basketball, track and field, helping to analyze and detect athletes' trajectories.
- How to use the Motion Trajectory Video Tracking Dataset for precise video analysis?
- The Motion Trajectory Video Tracking Dataset can be used with video analysis software to achieve precise analysis by marking key nodes and trajectories of athletes.
- What are the applications of this dataset in motion detection tasks?
- In motion detection tasks, this dataset can be used for real-time tracking of athletes' movements, analyzing game strategies, and optimizing training methods.
- What is the source of the Motion Trajectory Video Tracking Dataset?
- The Motion Trajectory Video Tracking Dataset typically comes from professional sports event recordings or videos collected with tracking equipment.
- How to effectively analyze sports video data used for machine learning model training?
- By feature extraction and data annotation, sports video data can be fed into machine learning models for effective motion pattern recognition and analysis.
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Verified for Enterprise UseCite this Work
@dataset{Mobiusi2026,
title={Motion Trajectory Video Tracking Dataset},
author={MOBIUSI INC},
year={2026},
url={https://www.mobiusi.com/datasets/5a2037d4e01b9853c392e9911b2fe2a6},
urldate={2026-02-04},
keywords={video tracking dataset, motion analysis dataset, content media video analysis},
version={1.0}
}Using this in research? Please cite us.
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