Multi-view learning for visual violence recognition with maximum entropy discrimination and deep features.

•We apply multi-view learning to violent behavior recognition of still images.•A violence image recognition database is constructed and made public.•We propose an MVMED+ model for learning with different numbers of views.•A sequential minimal optimization algorithm is provided for efficient training.•The proposed model outperforms multiple baselines.