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Keypoint Annotation
Supercharge your ML models with our Keypoint Annotation services. Our experts ensure precise labeling, enhancing AI application performance and reliability.
Defining Keypoint Annotation
Keypoint annotation assigns unique numbers to interconnected points, providing a precise way to track variations in objects with consistent structures, like human figures. The output comprises ordered x, y coordinates for easy interpretation.
Where is Keypoint Annotation Commonly Applied?
Keypoint annotations find diverse applications in:
Movement Tracking and Prediction:
Human Body Parts Detection
Gesture and Facial Recognition
Pose Identification for AR/VR
Sign Language Transcription
Additionally, keypoint annotations are employed in specific industries such as:
Medical: Tracking instruments in robotic-assisted surgery.
Geospatial: Monitoring crane movement on construction sites.
Automotive: Tracking pedestrian movement on streets.
Industrial: Detecting hand gestures of manufacturing workers.
Agriculture: Tracking the movement of livestock.
Retail: Detecting shopper actions in smart supermarkets.
Advantages & Disadvantages
Advantages:
Efficiency and Ease of Adjustment:Once the skeleton is established, adjusting nodes makes the annotation process more efficient and user-friendly.
Preventive Annotation:Keypoints act as guides, reducing the likelihood of annotators overlooking nodes in the sequence.
Useful for Specific Structures:Well-suited for objects with a consistent and regular structure, providing accurate annotations.
Application in Various Fields:Versatile usage, especially in movement tracking, human body detection, gesture recognition, and AR/VR pose identification.
Disadvantages:
Dependence on Regular Object Structure:Effectiveness is contingent on objects having a uniform and regular structure, limiting applicability in diverse scenarios.
Challenges in Visibility:Instances where some keypoints are not visible, especially in edge cases (e.g., a turned human), may lead to confusion in model interpretation.
Specialized Use Cases:Limited usefulness in scenarios where the object’s structure does not align with the requirements of keypoint annotation.
Keypoint Annotation Guidelines
- Handling Hidden Keypoints:
- Clearly define whether hidden keypoints should be deleted or if their positions need to be deduced by the labeler. This ensures consistent annotation practices.
- Clearly define whether hidden keypoints should be deleted or if their positions need to be deduced by the labeler. This ensures consistent annotation practices.
- Define Proportions for Accuracy:
- Specify proportions, such as expected edge length, to guide labelers and prevent the detection of keypoints that fall outside reasonable parameters.
- Specify proportions, such as expected edge length, to guide labelers and prevent the detection of keypoints that fall outside reasonable parameters.
- Clarify “Left” and “Right” Guidelines:
- Establish clear guidelines on determining “left” and “right,” specifying whether annotators should label data from their perspective or from the object’s perspective. This reduces errors in interpretation and ensures consistency in annotations.
Trusted Annotation Platforms
How Subul Data Annotation Works For You
Personalized and Fully Managed
Get a dedicated project manager to handle everything from guidelines to quality control, ensuring a seamless experience from start to finish.
Multilayer Quality Control
Experience the assurance of multi-tiered QC processes, including peer review and expert checks, guaranteeing a minimum accuracy of 98%.
Diverse and Scalable Workforce
Access a diverse team of industry experts, assembled within 72 hours, tailored to fit your project's specific needs and scale.
Unbiased and Compliant
Rely on our rigorously trained workforce for unbiased data, perfectly aligned with international privacy and AI standards.
Express Delivery
Benefit from our dynamic workforce, capable of rapidly scaling up to meet tight deadlines and ensure swift project delivery.
Direct Social Impact
Make a difference with every project; our entire workforce comes from refugee and disadvantaged backgrounds, contributing to social goals.
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Types of Our Data Annotation Serveries
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Frequently asked questions
What sets Keypoint Annotation apart from other techniques?
Keypoint Annotation labels specific points for tasks like object detection.
How are obscured keypoints handled?
Clear instructions guide annotators on handling visibility challenges.
Can Keypoint Annotation be used for irregular structures?
It's most effective for consistent structures, impacting accuracy otherwise.
What guidelines ensure consistency in labeling "left" and "right" keypoints?
Clear instructions prevent errors, specifying annotator or object perspective.
Are there criteria to maintain accuracy in annotation?
Defining proportions, like expected edge length, guides annotators for precision.
How does Keypoint Annotation enhance machine learning efficiency, and where is it beneficial?
It boosts ML models, especially in healthcare, automotive, robotics, and retail for tasks like movement tracking and gesture recognition.