Large-Scale Egocentric Video Dataset

This dataset is a large-scale collection of egocentric video data designed to support research, development, and evaluation of computer vision, video understanding, human activity recognition, behavioral analysis, and multimodal AI systems.

The corpus contains first-person video recordings captured from an egocentric perspective, providing a realistic representation of human interactions, activities, object usage, environmental context, and day-to-day tasks. The dataset enables the development of AI systems capable of understanding visual experiences from a human viewpoint.

The first-person perspective provides valuable context for analyzing actions, hand-object interactions, scene transitions, task execution, and environmental awareness, making the dataset suitable for a broad range of computer vision and video intelligence applications.

• Egocentric Vision
• First-Person Video Understanding
• Human Activity Recognition
• Action Recognition
• Behavioral Analysis
• Wearable AI Systems
• Scene Understanding
• Human-Centered Computer Vision
• Video Analytics
• Visual Understanding
• Multimodal AI Applications
• Robotics and Embodied AI
• Human-Object Interaction Analysis

• Large-scale first-person video recordings
• Real-world egocentric perspectives
• Human activity and interaction data
• Diverse environments and scenarios
• Natural motion and scene transitions
• Wearable-camera style recordings
• Rich contextual visual information
• Suitable for training and evaluation workflows

The dataset captures a wide range of real-world activities and interactions, including:

• Daily activities
• Human-object interactions
• Indoor and outdoor environments
• Task-oriented workflows
• Environmental exploration
• Contextual scene understanding
• Activity sequencing and event analysis
• Natural human behavior patterns

The diversity of activities and environments helps support the development of robust computer vision systems capable of understanding dynamic real-world situations.

The dataset is designed to support modern AI and computer vision workflows, including activity recognition, video understanding, action segmentation, scene analysis, visual reasoning, and multimodal learning.

Organizations can utilize this dataset for developing wearable AI solutions, intelligent assistants, robotics systems, human behavior analysis platforms, video analytics solutions, and next-generation vision-based AI applications.

The corpus can support:

• Egocentric video research
• First-person vision systems
• Embodied AI development
• Human activity modeling
• Human-centered AI applications
• Visual perception research
• Context-aware AI systems
• Intelligent monitoring and analytics solutions

The dataset consists of first-person video recordings curated to provide diverse visual contexts, activities, and interaction patterns. The content has been organized to support large-scale machine learning, computer vision, and AI development workflows.

This listing contains sample data intended for research, evaluation, and educational purposes. Enterprise licensing and access to the complete dataset are available upon request.

Email:  datareq@infobay.ai  Phone: +91 8303174762