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Commercial
Facial Keypoint Detection Dataset
Large-scale face dataset for facial keypoint detection containing nearly 200,000 annotated images of diverse individuals displaying facial emotions across various age groups and scenes. Designed for training facial keypoint detection, emotion recognition, expression analysis, and facial recognition models using rich facial features and metadata to support advanced computer vision applications.
-
- photos
- 5,000+
-
- landmarks
- 15
- Data annotation
- Computer Vision
- Facial Recognition
- Anti-spoofing
- Machine learning
- Data annotation
- Computer Vision
- Facial Recognition
- Anti-spoofing
- Machine learning
Large-scale face dataset for facial keypoint detection containing nearly 200,000 annotated images of diverse individuals displaying facial emotions across various age groups and scenes. Designed for training facial keypoint detection, emotion recognition, expression analysis, and facial recognition models using rich facial features and metadata to support advanced computer vision applications.
- Data annotation
- Computer Vision
- Facial Recognition
- Anti-spoofing
- Machine learning
-
- photos
- 5,000+
-
- landmarks
- 15
Dataset Info
| Characteristic | Data |
| Description | close-up images of faces with annotated data for facial recognition |
| Data types | Image |
| Tasks | Facial recognition, Computer Vision |
| Number of images | 5,000+ |
| Number of landmarks | 15 |
| Landmarks | Left eye, the closest point to the nose, Left eye, pupil's center, Left eye, the closest point to the left ear, Right eye, the closest point to the nose, Right eye, pupil's center, Right eye, the closest point to the right ear, Left eyebrow, the closest point to the nose, Left eyebrow, the closest point to the left ear, Right eyebrow, the closest point to the nose, Right eyebrow, the closest point to the right ear, Nose, center, Mouth, left corner point, Mouth, right corner point, Mouth, the highest point in the middle, Mouth, the lowest point in the middle |
| Labeling | Metadata (ID, gender) |
| Gender | Male, Female |
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Technical
Characteristics
| Characteristic | Data |
| Image extension | JPG |
| Extension of labeling file | JSON |
Dataset Use Cases
FAQs
How was the dataset collected?
The dataset was created through crowdsourced data collection, where contributors provided high-quality facial images under different lighting and pose conditions. This ensures that the dataset covers a wide range of human faces, head poses, and facial expressions for robust model training.
What are the sources of data for Unidata datasets?
Facial Keypoint Detection Dataset was collected by the Unidata team using a crowdsourcing service. All images feature real human faces captured under various lighting and pose conditions to provide diverse training data for facial recognition systems.
Can I request a sample of the dataset before purchasing?
Yes. Unidata provides free dataset samples for evaluation purposes. This allows you to review the image quality, annotation accuracy, and facial landmark labeling before purchasing the full version for facial keypoints detection or emotion recognition projects.
Is it possible to request a custom dataset?
Yes. Unidata offers custom datasets designed to meet your specific needs. You can request additional facial landmarks, different demographic distributions, or annotation formats to support your recognition algorithms and machine learning experiments.
How are Unidata datasets licensed?
Unidata datasets follow a dual-licensing model. Free samples are available for testing and validation, while the full dataset is available for purchase for research, training, or commercial use.
Do Unidata datasets follow GDPR or other data privacy regulations?
Yes. All datasets are developed in full compliance with GDPR and relevant data protection laws. The data is collected ethically through legal channels, ensuring the responsible handling of personal and biometric information.
How are Unidata datasets stored?
Unidata securely stores all datasets on AWS cloud infrastructure. This ensures data protection, high availability, and scalability, following ISO 27001 and ISO 27701 standards to maintain international information security and privacy management compliance.
Why are facial landmarks important for machine learning?
Facial landmarks provide precise reference points that allow AI models to understand the structure and movement of a face. Accurate landmark localization improves downstream tasks such as facial recognition, emotion analysis, face tracking, and biometric verification.
Still have questions about using Unidata datasets?
Read our user-guides
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