SMAGNet: Scaled Mask Attention Guided Network for Vision-based Gait Analysis in Multi-person Environments

Clinical gait analysis plays a key role in diagnosing and managing neurodegenerative diseases such as Parkinson's disease. In recent years, vision-based gait analysis methods have emerged as promising non-invasive approaches to quantify gait characteristics. However, most methods assume single-person situations, but multi-person situations are more common in realworld medical settings. In this paper, we propose a novel mask-guided attention model called a Scaled Mask Guided Attention Network (SMAGNet), which exploits a target person