Ciampi L., Foszner P., Messina N., Staniszewski M., Gennaro C., Falchi F., Serao G., Cogiel M., Golba D., Szczesna A., Amato G.
Violence detection Action recognition Fight detection Video surveillance Deep learning Violence detection benchmark
Automatic detection of violent actions in public places through video analysis is difficult because the employed Artificial Intelligence-based techniques often suffer from generalization problems. Indeed, these algorithms hinge on large quantities of annotated data and usually experience a drastic drop in performance when used in scenarios never seen during the supervised learning phase. In this paper, we introduce and publicly release the Bus Violence benchmark, the first large-scale collection of video clips for violence detection in public transport, where some actors simulated violent actions inside a moving bus in changing conditions such as background or light. Moreover, we conduct a performance analysis of several state-of-the-art video violence detectors pre-trained with general violence detection databases on this newly established use case. The achieved moderate performances reveal the difficulties in generalizing from these popular methods, indicating the need to have this new collection of labeled data beneficial to specialize them in this new scenario.
Source: Sensors (Basel) 22 (2022). doi:10.3390/s22218345
Publisher: Molecular Diversity Preservation International (MDPI),, Basel
@article{oai:it.cnr:prodotti:472912, title = {Bus violence: an open benchmark for video violence detection on public transport}, author = {Ciampi L. and Foszner P. and Messina N. and Staniszewski M. and Gennaro C. and Falchi F. and Serao G. and Cogiel M. and Golba D. and Szczesna A. and Amato G.}, publisher = {Molecular Diversity Preservation International (MDPI),, Basel }, doi = {10.3390/s22218345 and 10.3390%2fs22218345}, journal = {Sensors (Basel)}, volume = {22}, year = {2022} }