Facial Emotion Recognition Dataset for Children with Autism
Description
The Facial Emotion Recognition Dataset for Children with Autism (FER-Autism) is a curated and augmented image collection developed to advance research in Autism Spectrum Disorder (ASD) detection and facial emotion recognition using computer vision and deep learning techniques. The dataset contains 1,200 training images and 220 testing images, carefully selected to ensure diversity and representativeness across emotion categories. It is an enhanced and restructured version of an existing Autism Facial Recognition Dataset. Through systematic data augmentation and a balanced train/test split, this dataset provides a robust foundation for building accurate and generalizable models capable of identifying emotional patterns and ASD-related facial cues in children. This dataset was developed under the supervision of Prof. Shimaa Elgamal, Lecturer of Neurology, Faculty of Medicine, Kafrelsheikh University (Google Scholar Profile ). Data Augmentation To enhance diversity and robustness, a comprehensive data augmentation pipeline was implemented using the Albumentations library. Each original image was augmented 10 times, introducing variations in geometry, color, brightness, and noise to simulate real-world conditions and reduce overfitting. Key Augmentation Techniques: Geometric: Horizontal flip and random rotation (±10°). Color & Brightness: Hue, saturation, and value shifts; gamma contrast adjustment. Noise & Quality: Gaussian blur and Gaussian noise. Resizing & Cropping: Random cropping and resizing to 224×224 pixels. These transformations strengthen the dataset’s capacity to train models that generalize well across different lighting, orientations, and environments. Emotion Classes The dataset includes six primary facial emotion categories representing a range of affective states in children: Natural Anger Fear Joy Sadness Surprise additional help links https://onlinelibrary.wiley.com/doi/10.1002/aur.70030?utm_source=chatgpt.com https://arxiv.org/abs/2307.13706?utm_source=chatgpt.com
Files
Institutions
- Kafrelsheikh University