We present a proof-of-concept for detecting upper-body joints position from sleep images, even when blankets occlude the person. Our method improves relative precision by 115% compared to standard models. While absolute performance remains modest, this work establishes a first step towards clinically applicable, video-based pose estimation during sleep. Future work should integrate contextual priors and expand annotated sleep datasets.
Dorier et al. (Fri,) studied this question.