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.
|Title of host publication||Proceedings of the 29th Conference of Open Innovations Association FRUCT, FRUCT 2021|
|Editors||Sergey Balandin, Yevgeni Koucheryavy, Tatiana Tyutina|
|Publisher||IEEE Computer Society|
|Number of pages||6|
|State||Published - 12 May 2021|
|Event||29th Conference of Open Innovations Association FRUCT, FRUCT 2021 - Virtual, Tampere, Finland|
Duration: 12 May 2021 → 14 May 2021
|Name||Conference of Open Innovation Association, FRUCT|
|Conference||29th Conference of Open Innovations Association FRUCT, FRUCT 2021|
|Period||12/05/21 → 14/05/21|
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© 2021 FRUCT.