Egocentric videos
Collection
4 items • Updated
filename stringclasses 6
values | relative_path stringclasses 6
values | extension stringclasses 3
values | file_type stringclasses 1
value | file_bytes unknown | file_size_bytes int64 510k 109M |
|---|---|---|---|---|---|
a67743-H-0152.aac | Sample - 01/a67743-H-0152.aac | .aac | image_or_graphic | "//FgQEAA/AEyNa50yEsNWZKx18r676uwamqrM1axdSSQQuFMPNVOai5f8VnioAXH4rHPY+W8dceSwPZ83czYKJyzxPwoIrxxHS6(...TRUNCATED) | 1,440,261 |
a67743-H-0152.mp4 | Sample - 01/a67743-H-0152.mp4 | .mp4 | image_or_graphic | "AAAAHGZ0eXBpc29tAAACAGlzb21pc28ybXA0MQAAAAhmcmVlBlfRrm1kYXQAAAAiQAEMAf//AWAAAAMAsAAAAwAAAwB7rAwAAAM(...TRUNCATED) | 106,481,543 |
a67743-H-0152.txt | Sample - 01/a67743-H-0152.txt | .txt | image_or_graphic | "eyJ0X3VzIjoyNjgyODY1MzgxMiwiYWNjIjpbLTEuMjI1ODMxLDAuMzIwODIzLDguOTY4Njc5XSwiZ3lybyI6WzAuNDIzNzMxLDA(...TRUNCATED) | 510,108 |
a05868-H-0046.aac | Sample - 02/a05868-H-0046.aac | .aac | image_or_graphic | "//FgQEAA/AEyNa30qJMligLaxNYvLrWJUuqXWmAbEJDmzrnJDlz6tw/pJt9l566o5o5lfuyq86gyl1DeWITf1G49jQ3lDmuUAem(...TRUNCATED) | 1,439,744 |
a05868-H-0046.mp4 | Sample - 02/a05868-H-0046.mp4 | .mp4 | image_or_graphic | "AAAAGGZ0eXBtcDQyAAAAAG1wNDJpc29tBnjAl21kYXQAAAAiQAEMAf//AWAAAAMAsAAAAwAAAwB7rAwAAAMABAAAAwB6qAAAACx(...TRUNCATED) | 108,628,917 |
a05868-H-0046.txt | Sample - 02/a05868-H-0046.txt | .txt | image_or_graphic | "eyJ0X3VzIjo4MTA0ODQxNTk1LCJhY2MiOlstMS45Mjk3MjcsMi4yNjk3MDMsLTkuNjkxNzI5XSwiZ3lybyI6Wy0wLjAzNTEzMyw(...TRUNCATED) | 511,149 |
Mono IMU Egocentric Dataset
Overview
The Mono IMU Egocentric Dataset is a collection of egocentric recording data containing video and IMU (Inertial Measurement Unit) sensor data. It is intended for researchers, developers, and organizations exploring sensor-based perception, egocentric data analysis, computer vision, robotics, and related AI applications.
The dataset combines video files with IMU sensor data from an egocentric recording setup. The available file formats include .mp4, .aac, and .txt.
Publicly available samples provide an opportunity for prospective users to inspect the available data. Detailed information about sensor specifications, annotation schemes, recording environments, dataset size, and full-dataset access conditions has not yet been confirmed.
Dataset Highlights
- Egocentric recording data: Data collected from an egocentric recording setup.
- Video and sensor data: Includes video and IMU sensor data.
- Multiple file formats: Includes
.mp4,.aac, and.txtfiles. - Public samples: Sample files are publicly available.
Dataset Features
| Feature | Confirmed Information |
|---|---|
| Dataset name | Mono IMU Egocentric Dataset |
| Recording perspective | Egocentric |
| Data modalities | Video and IMU sensor data |
| File formats | MP4, AAC, TXT |
| Sensor specifications | Not yet confirmed |
Dataset Structure
Mono_IMU_Egocentric_Dataset/
├── [MP4 video files]
├── [AAC files]
└── [TXT files]
AI Tasks Supported
The dataset may be relevant to research and development involving:
- Egocentric video analysis.
- Video and inertial sensor data analysis.
- Multimodal machine learning.
- Computer vision research.
- Sensor-based perception.
- Robotics and autonomous systems research.
- Human-motion research.
- AR/VR-related research.
Applications
Potential areas of exploration include:
- AI and machine learning: Research involving video and sensor data.
- Computer vision: Analysis of visual information from an egocentric recording setup.
- Robotics: Research into perception using visual and inertial data.
- Autonomous systems: Investigation of sensor-based perception approaches.
- AR/VR development: Research into egocentric sensing and multimodal data processing.
- Human-motion research: Exploration of visual and inertial information in movement-related studies.
- Academic research: Development and evaluation of methods using egocentric recordings.
Industries and Research Areas
The dataset may be of interest to teams working in:
- Artificial intelligence and machine learning.
- Computer vision and video understanding.
- Robotics and autonomous systems.
- Augmented reality and virtual reality.
- Human-motion and sensor research.
- Multimodal data processing.
- Academic and applied research.
- Enterprise research and development.
These are potential audiences and research areas, not confirmed industry-specific coverage within the dataset.
Advantages
- Combines egocentric video and IMU sensor data.
- Includes multiple file formats for data inspection and processing.
- Offers publicly available samples for initial evaluation.
- May support research involving visual and inertial information.
- Is relevant to several research communities, including computer vision, robotics, AR/VR, and multimodal AI.
Intended Audience
The dataset may be relevant to:
- AI and machine learning researchers.
- Computer vision teams.
- Robotics teams.
- AR/VR developers.
- Autonomous systems teams.
- Human-motion researchers.
- Academic institutions.
- Enterprise research and development teams.
- Developers exploring multimodal video and sensor data.
Summary
The Mono IMU Egocentric Dataset contains egocentric video and IMU sensor data, with available files in MP4, AAC, and TXT formats. Publicly available samples provide an initial opportunity to examine the collection.
The dataset may be relevant to AI/ML research, computer vision, robotics, autonomous systems, AR/VR, and human-motion research. Further documentation of the sensor specifications, file relationships, annotations, and licensing terms will help prospective users assess its suitability for specific projects.
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