This paper introduces the Chinese Social Media Autism Children Dataset (CSMACD), a novel resource for autism spectrum disorder (ASD) research. CSMACD compiles high-definition, unobstructed frontal facial images of Chinese children (aged 6 months to 15 years) with ASD, sourced from mainstream social media platforms (e.g., Bilibili, Douyin, and Tencent Video). Videos were identified using ASD-related keywords (e.g., "autism," "Star Baby") and recommendation algorithms.
This dataset supports the LookCursor AI project, which implements eye-tracking-based cursor control using OpenCV and Dlib. The primary file included is shape_predictor_68_face_landmarks.dat, a pre-trained model used to detect and map 68 facial landmarks essential for tracking eye movements. The dataset enables accurate facial feature detection, which is critical for cursor movement based on eye gaze. This resource is valuable for researchers working on assistive technology, human-computer interaction (HCI), and computer vision applications.
