Anomaly detection has been used for decades to identify and extract anomalous
components from data. Many techniques have been used to detect anomalies. One of the …

Novelty detection is commonly referred as the discrimination of observations that do not
conform to a learned model of regularity. Despite its importance in different application …

The detection of abnormal behaviour in crowded scenes has to deal with many challenges.
This paper presents an efficient method for detection and localization of anomalies in …

Anomalies are rare and anomaly detection is often therefore framed as One-Class
Classification (OCC), ie trained solely on normalcy. Leading OCC techniques constrain the …

This paper proposes a fast and reliable method for anomaly detection and localization in
video data showing crowded scenes. Time-efficient anomaly localization is an ongoing …

We address an anomaly detection setting in which training sequences are unavailable and
anomalies are scored independently of temporal ordering. Current algorithms in anomaly …

This paper presents an overview of the state of the art of three different fields with the shared
characteristics of making use of a network of sensors, with the possible application of …

Understanding human behaviors is a challenging problem in computer vision that has
recently seen important advances. Human behavior understanding combines image and …

Abnormal Human Behavior Detection in Videos: A Review Page 1 Information Technology
and Control 2021/3/50 522 Abnormal Human Behavior Detection in Videos: A Review ITC 3/50 …

This paper presents an approach for detecting suspicious events in videos by using only the
video itself as the training samples for valid behaviors. These salient events are obtained in …