Human Videos Data Collection
Project Overview:
Objective
Human Videos Data Collection: To amass a comprehensive collection of human-centric videos. These videos are crucial in advancing AI technologies in areas such as facial recognition, behavioral analysis, activity recognition, and human-environment interaction.
Scope
We embarked on a journey to compile videos encapsulating the diverse spectrum of human life. Our collection spans various demographics, activities, settings, and expressions, ensuring a rich and multifaceted dataset.
Sources
- Public Areas: We collaborated with city councils to source videos from bustling public spaces, all while maintaining stringent privacy standards.
- Educational Institutions: Our partnerships with schools and universities allowed us to gather unique footage showcasing human interactions in academic settings.
- Events: We captured the essence of human gatherings through videos from various events like weddings, sports meets, and cultural festivals.
- Volunteer Contributions: A specially designed platform enabled volunteers to contribute videos, adhering to strict privacy guidelines and explicit consent protocols.
Data Collection Metrics
- Total Videos Collected: 120,000
- Public Area Footage: 35,000
- Educational Videos: 25,000
- Event Footage: 30,000
- Volunteer Submissions: 30,000
Annotation Process
Stages
- Demographic Data: Videos are annotated with relevant information such as age group, gender, and ethnicity of the participants.
- Activity Annotation: Videos are categorized based on the primary activity observed (e.g., dancing, conversing, studying, playing).
- Setting & Context: Videos are tagged with descriptors of the environment (indoors, outdoors, urban, rural) and other contextual details.
Annotation Metrics
- Demographic Annotations: 120,000
- Activity Annotations: 120,000
- Setting Tags: 120,000
Quality Assurance
Stages
Video Quality Review:Â A dedicated team ensures that the videos maintain a standard of clarity, stability, and resolution.
Privacy Protocols:Â Rigorous checks are implemented to ensure no private or identifiable information is inadvertently captured. Faces in public spaces are blurred or anonymized unless explicit permission is obtained.
Metadata Accuracy:Â A subset of videos undergoes a secondary review to confirm the accuracy of annotations.
QA Metrics
- Videos Enhanced for Quality: 12,000
- Full-Spectrum Privacy Checks: 120,000
- Metadata Audit Samples: 24,000
Conclusion
Through the Human Videos Data Collection Initiative, We has significantly contributed to the evolution of human-centric AI applications. With our extensive dataset, meticulous annotation process, and unwavering commitment to privacy and quality, we are setting new standards in AI data collection and annotation.
Quality Data Creation
Guaranteed TAT
ISO 9001:2015, ISO/IEC 27001:2013 Certified
HIPAA Compliance
GDPR Compliance
Compliance and Security
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