Sign4all: a Spanish Sign Language Dataset

Signs were performed from a neutral starting position and followed a structured protocol for consistency. Recordings were conducted in a controlled indoor environment with stable lighting and no clothing restrictions, ensuring realistic visual diversity.All signs are dynamic (in-motion) gestures. Each was recorded approximately 20 times per hand.

The camera was fixed at a height of 117 cm, and participants stood at variable distances (100–170 cm) to account for individual height differences.Data structure and formatThe dataset is organized into four versions:RGB Original: Raw segmented videos without background removal or normalization.RGB Normalized: Background-cropped, square videos temporally normalized to 48 frames.RGB Normalized + Augmentation: Additional visual augmentations applied.Skeletal Keypoints: 48×100 matrices per sample, representing 2D keypoints in HDF5 format.The RGB samples are distributed using AVI format.Use cases and reusabilityThe Sign4all dataset supports a variety of applications in Sign Language Technology:Isolated Sign Language RecognitionSkeletal-based gesture recognitionSigner-independent recognition model trainingResearchers can use RGB or skeletal data directly with deep learning models in PyTorch, TensorFlow or other frameworks.

Due to privacy concerns, dataset access is restricted and requires a Data Usage Agreement (DUA) request.