Commercial

Open Palm Hand Images Dataset

It is a high-quality open palm dataset containing 6,000 annotated human palm images captured from both right and left hands using front and rear cameras. Designed for hand detection, palm recognition, and gesture analysis, this palm dataset provides diverse training data with metadata on age, gender, and ethnicity for accurate computer vision model training.

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  • Images
    6 000
Open Palm Hand ML Dataset
  • Image Processing
  • Machine Learning
  • Hand Recognition
  • Forensics
  • Computer Vision

It is a high-quality open palm dataset containing 6,000 annotated human palm images captured from both right and left hands using front and rear cameras. Designed for hand detection, palm recognition, and gesture analysis, this palm dataset provides diverse training data with metadata on age, gender, and ethnicity for accurate computer vision model training.

Get in touch
  • Image Processing
  • Machine Learning
  • Hand Recognition
  • Forensics
  • Computer Vision
  • Images
    6 000

Technical
Characteristics

Characteristic Data
Description Open palm images designed for training and evaluating hand-based identification algorithms.
Data types Image
Tasks Hand Recognition, Computer Vision
Total number of files 6 000
Number of files in a set 12 (6 image of right hand, 6 image of left hand)
Labeling Metadata (Age, gender, ethnicity, profession (or previous job), device, dominant hand)
Gender Male, Female
Source and collection methodology: Data was collected via crowdsourcing platforms.

Dataset Use Cases

  • Biometric Authentication and Security

    Enhancing Palm Recognition and Hand Verification Systems

    Open Palm Hand Images Dataset supports the development of palm recognition and hand detection systems used in biometric authentication. With high-quality human palm images of both right and left hands, it provides reliable training data for model training, helping improve accuracy and security in identity verification and access control applications.

  • Gesture Recognition and Human-Computer Interaction

    Training AI Models for Gesture-Based Interfaces

    This hand dataset enables gesture recognition research by offering thousands of annotated hand poses and palm movements. It helps train deep learning models to interpret hand gestures, supporting applications in augmented reality, gaming, and touchless device control, where accurate pose estimation and motion tracking are essential.

  • Robotics and Motion Analysis

    Improving Robotic Perception and Manipulation Systems

    The palm dataset provides a valuable foundation for robotic vision systems to analyze hand movements and keypoints. By using this dataset comprising diverse palm images captured from multiple angles, robots can better recognize human hand positions, improving coordination, safety, and interaction in collaborative robotic environments.

  • Medical and Rehabilitation Research

    Analyzing Hand Poses for Motor Function Assessment

    Researchers use this hand images dataset to study hand gestures, fingers alignment, and pose representation in medical diagnostics. It supports pose estimation models that help evaluate motor function recovery, offering an objective tool for rehabilitation analysis and hand tracking in healthcare technology development.

FAQs

What is included in this dataset?
This dataset includes 6,000 labeled images featuring both right and left hands in open-palm poses. Each subject contributes 12 images (6 of each hand), annotated with metadata such as age, gender, ethnicity, dominant hand, and device used.
How was the data collected?
The dataset was gathered via crowdsourcing platforms, where participants submitted high-quality images captured with front and rear smartphone cameras. This approach ensured diversity in lighting conditions, hand sizes, and skin tones, providing robust training data for hand recognition systems.
Can I request a sample of the dataset before purchasing or downloading it?
Yes. Unidata provides free sample images from Open Palm Hand Images Dataset so you can evaluate image quality, labeling accuracy, and camera diversity. This allows you to confirm the dataset’s suitability for your hand detection or gesture recognition model before purchase.
How are Unidata datasets licensed?
Unidata datasets follow a dual-licensing model: free samples are provided for testing and evaluation, while full datasets are available for purchase. This allows organizations to assess dataset relevance before committing to full acquisition.
Do Unidata datasets follow GDPR or other data privacy regulations?
Yes. All Unidata datasets are developed in full compliance with GDPR and global data protection laws. The company ensures that all personal and biometric data is lawfully sourced, anonymized, and ethically managed.
How are Unidata datasets stored?
All datasets are securely stored on AWS cloud infrastructure, providing high availability, scalability, and privacy protection. Unidata’s data management adheres to ISO 27001 and ISO 27701 standards, ensuring safe and compliant handling of sensitive biometric information.
How long does it take to receive the dataset?
After submitting a request, Unidata will contact you to confirm dataset details and complete the required agreements. Once payment is processed, the dataset is typically delivered within 3 to 10 business days via secure cloud access.
Is this a real-world dataset or synthetic data?
This is a real-world dataset featuring genuine human hand images captured by real participants.
Still have questions about using Unidata datasets? Read our user-guides

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