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Irregular Events Detection in Videos using Machine Learning Techniques

Abstract: Video analytics for detecting events using machine learning is designed and developed to analyze and detect patterns in the videos. Especially in the field of criminal forensics where a video needs to be analyzed to find out what abnormal events are happening in it and who caused it and how it was caused. This is an easy task for a human as they can recognize criminal events easily but not machines. The objective is to automatically detect the irregular events in videos like burglary, fighting, arson and explosion using a CNN model by preprocessing the videos into frames and extracting information from these frames and also to train the model so that it can also detect normal events. The results of this work shows that the model detects irregular events in videos with high accuracy