System and Method for Detecting Anomalies in Video using a Similarity Function Trained by Machine Learning

摘要

A system for video anomaly detection includes an input interface configured to accept an input video of a scene, and a memory configured to store training video patches of a training video of the scene capturing normal activity in the scene, and store a neural network trained to compare two video patches to declare the compared video patches as similar or dissimilar. The system also includes a processor configured to partition the input video into input video patches, compare, using the neural network, each input video patch with corresponding training video patches retrieved from the memory to determine if each input video is similar to at least one corresponding training video patch, and declare an anomaly when at least one input video patch is dissimilar to all corresponding training video patches.