Resumen
Citizen insecurity is directly related to interpersonal physical violence, there are algorithms that allow detecting violence in videos; therefore, it is necessary to know which is the best model for detecting violence. For this research, three convolutional neural network models were compared: Xception, InceptionV3 and VGG16 each together with a recurrent LSTM network, to find out which of the models is the best for the detection of interpersonal violence in videos. The three models were trained using the Real Life Violence Situations dataset, then violence and non-violence were classified, as a result, the InceptionV3 model is the best model, managing to classify with an accuracy of 94% compared to the VGG16 and Xception models, which obtained 88% and 93% respectively. Therefore, we recommend the InceptionV3 model for the detection of interpersonal physical violence in citizen security videos.
Idioma original | Inglés |
---|---|
Título de la publicación alojada | Proceedings of the 29th Conference of Open Innovations Association FRUCT, FRUCT 2021 |
Editores | Sergey Balandin, Yevgeni Koucheryavy, Tatiana Tyutina |
Editorial | IEEE Computer Society |
Páginas | 81-86 |
Número de páginas | 6 |
ISBN (versión digital) | 9789526924458 |
DOI | |
Estado | Publicada - 12 may. 2021 |
Evento | 29th Conference of Open Innovations Association FRUCT, FRUCT 2021 - Virtual, Tampere, Finlandia Duración: 12 may. 2021 → 14 may. 2021 |
Serie de la publicación
Nombre | Conference of Open Innovation Association, FRUCT |
---|---|
Volumen | 2021-May |
ISSN (versión impresa) | 2305-7254 |
Conferencia
Conferencia | 29th Conference of Open Innovations Association FRUCT, FRUCT 2021 |
---|---|
País/Territorio | Finlandia |
Ciudad | Virtual, Tampere |
Período | 12/05/21 → 14/05/21 |
Nota bibliográfica
Publisher Copyright:© 2021 FRUCT.