A novel random forests based class incremental learning method for activity recognition

•A novel separating axis theorem (SAT) based splitting strategy is proposed.•By combining SAT based splitting strategy and traditional splitting strategy, we propose a novel class incremental random forests algorithm (CIRF).•Performance of CIRF on three public activity recognition datasets is competitive and robust.