SIGNO-PERU-FER: A Multimodal RGB-D Dataset of Visuo-Gestural Facial Expressions in Peruvian Sign Language
Description
SIGNO-PERU-FER is a multimodal RGB-D dataset of dynamic Visuo-Gestural Facial Expressions (VGFEs) in Peruvian Sign Language (LSP), designed to support research on non-manual sign language recognition, multimodal facial behavior modeling, and inclusive AI systems. It comprises 1,256 synchronized RGB-D video sequences from 16 native LSP signers across 14 VGFE categories selected for their visual similarity and classification challenges. Each sequence includes RGB video (1920×1080, 30 fps), depth maps (512×512), and 468 3D facial landmark points captured with an Azure Kinect DK under controlled laboratory conditions.#Category#Category1Annoyed8No2Bored9Sad3Crying10Smells bad4Disgust11Surprise5Happy12Thief6I don't know13Tired7Let's see14YesThe SIGNO-PERU-FER dataset is archived in Zenodo under restricted access due to the re-identification risk inherent to audiovisual recordings. Access is provided via Zenodo's access-request workflow and requires acceptance of the SIGNO-PERU-FER Data Use Agreement (DUA), which includes named-user registration and data protection terms. To request access, download theSIGNO-PERU-FER_AccessRequestForm_DUAfrom this record, complete it, and email the signed form to [email protected] or [email protected].
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Publication Details
Subfield
Computer Vision and Pattern Recognition
Field
Computer Science
Domain
Physical Sciences
Confidence Score
46%
Source
Scholar Data Model