USE CASE
Keypoints Image Annotation
Keypoints-labeling of facial points on people's photos. The dataset solves the tasks of face recognition and emotion analysis
Data Labeling
Highlighting objects in photos to train systems to recognize and interpret them
Facial Recognition
Process of identifying or verify a person identity using facial features
Emotion Recognition
Process of identifying and classifying human emotional states
Computer Vision
Ability of a machine to interpret, analyze, and understand visual data
1500
images
2 weeks
project duration
Our Partners
TECHNICAL SPECIFICATIONS
Photos and selfies of people are collected using parsing and crowdsourcing
Each face is placed using 15 keypoints
APPLICATION AREAS OF THE DATASET
Emotion recognition:
Computer vision for automatic detection of human emotions in photographs
Automatic image editing:
Keypoints annotation for automatic editing or enhancement of photographs
Biometric identification:
Computer vision and classification for developing biometric identification systems that can identify unique facial features of a specific individual
Medicine:
Keypoint annotation for the analysis of patients' facial characteristics, diagnosis of various diseases, monitoring of patients' emotional state, and tracking overall health condition
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Why
Training Data
- Quality Assurance:
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Enhanced Data Accuracy
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Consistency in Labels
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Reliable Ground Truth
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Mitigation of Annotation Biases
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Cost and Time Efficiency
- Data Security and Confidentiality:
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GDPR Compliance
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Non-disclosure agreement
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Data Encryption
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Multiple data storage options
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Access Controls and Authentication
- Expert Team:
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6 years in industry
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35 top project managers
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40+ languages
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100+ countries
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250k+ assessors
- Flexible and Scalable Solutions:
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24/7 availability of customer service
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100% post payment
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$550 minimum check
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Variable Workload
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Customized Solutions
Team leads project
Wadim Starosotnikow
Senior quality control manager
Arthur Kazukevich
Python-developer
Maria Kuzmina
Project manager