Human Videos Dataset
Project Overview:
Objective
The Human Videos Dataset project aims to enhance technologies for recognizing human activities. This dataset helps in creating advanced algorithms that can understand and interpret various human actions.
Scope
The project collects and annotates human activity videos. Volunteers, public domain datasets, and professional actors provide these videos, ensuring a diverse and comprehensive collection. To improve readability and clarity, I have rewritten the text using active voice, added transition words, and simplified complex words.
Sources
- Volunteers: 15,000 videos
- Public Domain Datasets: 7,000 videos
- Professional Actors: 3,000 videos
Data Collection Metrics
Total Video Recordings for Human Activity Recognition: 25,000 videos
Annotation Process
Stages
- Activity Labeling: We meticulously annotate each video to identify the specific human activities performed.
- Metadata Annotation: We log important metadata for each video, such as the recording date, duration, and contextual notes.
Annotation Metrics
- Videos with Activity Labels: 25,000
- Metadata Annotation: 25,000
Quality Assurance
Stages
Annotation Verification: A team of experts in human activity recognition reviews and validates the annotations for accuracy.
Data Quality Control: The team systematically removes videos that are unclear, of low quality, or irrelevant.
Privacy and Consent: We strictly adhere to privacy laws and ethical guidelines, ensuring all data is collected with informed consent.
QA Metrics
- Verified Annotations: 2,500 (10% of total)
- Data Cleansing: Ongoing removal and refinement of dataset quality.
Conclusion
The Human Videos Dataset is a key resource for improving human activity recognition technologies. With a wide variety of labeled videos and strict quality checks, this dataset is set to change how machines understand and interact with human activities. As a result, it is a crucial step towards creating more user-friendly and responsive systems that can easily fit into everyday life.
Quality Data Creation
Guaranteed TAT
ISO 9001:2015, ISO/IEC 27001:2013 Certified
HIPAA Compliance
GDPR Compliance
Compliance and Security
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