Towards scalable activity recognition
Long-Van Nguyen-Dinh, Ulf Blanke, Gerhard Tröster · 2013
Human activity recognition systems traditionally require a manual annotation of massive training data, which is laborious and non-scalable. An alternative approach is mining existing online crowd-sourced repositories for open-ended, free annotated training data. However, differences across data sources or in observed contexts prevent a crowd-sourced based model reaching user-dependent recognition rates.