UniDataPro/open-palm-hand-images

Palm dataset - 500,000 images

Dataset containing 500,000 human palm images. 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.

By leveraging this dataset, researchers and developers can advance computer vision models for highly accurate hand detection, palm recognition, and gesture analysis. - Get the data

Frequently Asked Questions

Who can benefit from this hand images dataset?

This hand images dataset is valuable for biometric authentication developers, AI researchers, forensic laboratories, academic institutions, and computer vision teams. It supports projects involving palm recognition, identity verification, liveness detection, presentation attack detection, and secure access systems. Organizations developing contactless biometric authentication or evaluating hand-based recognition algorithms can use the dataset to improve both recognition accuracy and resistance to spoofing attempts.

What types of hand samples are included in this open palm dataset?

The open palm dataset contains more than standard palm photographs. Each participant contributes a structured set consisting of six genuine palm images, two printed-hand images, and two replay samples. This combination enables researchers to develop and evaluate both hand recognition and presentation attack detection algorithms using consistent data collected from the same individual.

How was the open palm dataset collected?

The dataset was collected through crowdsourcing platforms using a structured acquisition process to ensure consistent image capture across participants.

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Dataset includes both right hands and left hands in various configurations, supporting advanced research in hand tracking and poses estimation.

Example of the data

Researchers can utilize this dataset to explore hand detection technology and recognition algorithms that aim to improve gesture analysis and hand tracking capabilities across various applications including security systems, human-computer interaction, and biometric authentication.

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