BDFE-6 (Bangladeshi Facial Expression Dataset)

Published: 30 June 2026| Version 1 | DOI: 10.17632/fd62n6bdxr.1
Contributors:
,
,

Description

The proposed BDFE-6 (Bangladeshi Facial Expression Dataset) is a six-class facial expression image dataset developed to facilitate research in facial expression recognition, affective computing, human–computer interaction, and deep learning-based computer vision applications. The dataset comprises 1,236 original RGB facial images collected from 277 unique participants affiliated with Daffodil International University (DIU), Bangladesh. The images are categorized into six emotion classes: Angry (152), Fear (135), Happy (276), Normal (277), Sad (221), and Surprise (175). To ensure consistency across experiments, all images were preprocessed and resized to a uniform resolution of 512 × 512 pixels. To improve the diversity of the training data and enhance the generalization capability of deep learning models, various data augmentation techniques, including horizontal flipping, rotation, scaling, translation, brightness adjustment, and other geometric transformations, were applied. Consequently, the dataset size was expanded from 1,236 original images to 4,944 augmented images while preserving the semantic integrity of each emotion class. All facial images were collected exclusively for research purposes from volunteers at Daffodil International University after obtaining written informed consent from every participant. The dataset collection protocol adhered to ethical research standards and received approval from the Institutional Review Board (IRB)/Ethics Committee of Daffodil International University, Reference No.: REC/FSIT/DIU/2026/2015. The dataset is intended to serve as a valuable benchmark for developing and evaluating machine learning, deep learning, transfer learning, and explainable AI (XAI)-based facial expression recognition systems.

Files

Steps to reproduce

Need to Unzip

Institutions

Categories

Computer Vision, Image Capture, Facial Recognition, Image Classification

Licence