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On the Benefit of Generative Foundation Models for Human Activity Recognition
Zikang Leng, Hyeokhyen Kwon, Thomas Plötz
In human activity recognition (HAR), the limited availability of annotated data presents a significant challenge. Drawing inspiration from the latest advancements in generative AI,…
On Attention Models for Human Activity Recognition
Vishvak S Murahari, Thomas Ploetz
Most approaches that model time-series data in human activity recognition based on body-worn sensing (HAR) use a fixed size temporal context to represent different activities. This…
Augmenting Bag-of-Words: Data-Driven Discovery of Temporal and Structural Information for Activity Recognition
Vinay Bettadapura, Grant Schindler, Thomaz Plotz +1
We present data-driven techniques to augment Bag of Words (BoW) models, which allow for more robust modeling and recognition of complex long-term activities, especially when the st…