Video Based

Video-based analysis is rapidly advancing as a tool for objective and automated assessment across diverse fields, moving beyond subjective human evaluation. Current research focuses on developing and validating deep learning models, often employing convolutional neural networks (CNNs) and recurrent neural networks (RNNs), sometimes enhanced with attention mechanisms or multi-task learning, to extract meaningful features from video data for tasks such as pose estimation, action recognition, and biometric measurement. This approach offers significant potential for improving healthcare diagnostics (e.g., scoliosis screening, newborn anthropometry), surgical training and evaluation, and even sports performance analysis by providing non-invasive, efficient, and quantitative assessments.