A Panoramic Review on Cutting-Edge Methods for Video Anomaly Localization

Abstract

Video anomaly detection and localization is the process of spatiotemporally localizing the anomalous video segment corresponding to the abnormal event or activities. It is challenging due to the inherent ambiguity of anomalies, diverse environmental factors, the intricate nature of human activities, and the absence of adequate datasets. Further, the spatial localization of the video anomalies (video anomaly localization) after the temporal localization of the video anomalies (video anomaly detection) is also a complex task. Video anomaly localization is essential for pinpointing the anomalous event or object in the spatial domain. Hence, the intelligent video surveillance system must have video anomaly detection and localization as key functionalities. However, the state-of-the-art lacks a dedicated survey of video anomaly localization. Hence, this article comprehensively surveys the cutting-edge approaches for video anomaly localization, associated threshold selection strategies, publicly available datasets, performance evaluation criteria, and open trending research challenges with potential solution strategies.

Keywords

• Deep learning
• explainable learning
• saliency detection
• statistical method
• video anomaly detection
• video anomaly localization