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Real-time monocular human pose estimation is an important sensing component for human-centered intelligent systems. While recent camera-based methods have achieved impressive accuracy, fundamental challenges persist, particularly when visual observations are incomplete, such as during lower-body occlusion or short out-...
LLMs increasingly support sensor-based human activity recognition (HAR) by linking motion signals with activity semantics and physical knowledge. Retrieval-augmented generation (RAG) grounds decisions in sensor examples and domain features, enabling training-free target-user inference with less dependence on raw numeri...
Motor rehabilitation and clinical biomechanical assessment rely on expert judgement to evaluate movement quality, pathological compensation, and spatiotemporal motor dynamics. Existing automated approaches mainly depend on conventional computer vision methods, such as skeletal keypoint-based analysis, but they prov...
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