Action Recognition Method

Action recognition, a core computer vision task, aims to automatically identify and classify human actions within video data. Current research heavily emphasizes multimodal approaches, integrating data from RGB images, depth sensors, human pose skeletons, and even human parsing (semantic segmentation of body parts), often leveraging convolutional neural networks (CNNs) and increasingly, transformer architectures for improved spatio-temporal feature extraction and modeling. These advancements are driving progress in diverse applications, including healthcare (e.g., cognitive assessment), robotics (e.g., handling occlusions), and human-computer interaction, with a growing focus on addressing challenges like open-set recognition and low-light conditions.