Video Anomaly Detection for Smart Surveillance
- URL: http://arxiv.org/abs/2004.00222v3
- Date: Sat, 11 Apr 2020 19:07:05 GMT
- Title: Video Anomaly Detection for Smart Surveillance
- Authors: Sijie Zhu, Chen Chen, and Waqas Sultani
- Abstract summary: Anomalies in videos are defined as events or activities that are unusual and signify irregular behavior.
The goal of anomaly detection is to temporally or spatially localize the anomaly events in video sequences.
This paper provides a brief overview of the recent research progress on video anomaly detection.
- Score: 13.447928371592557
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: In modern intelligent video surveillance systems, automatic anomaly detection
through computer vision analytics plays a pivotal role which not only
significantly increases monitoring efficiency but also reduces the burden on
live monitoring. Anomalies in videos are broadly defined as events or
activities that are unusual and signify irregular behavior. The goal of anomaly
detection is to temporally or spatially localize the anomaly events in video
sequences. Temporal localization (i.e. indicating the start and end frames of
the anomaly event in a video) is referred to as frame-level detection. Spatial
localization, which is more challenging, means to identify the pixels within
each anomaly frame that correspond to the anomaly event. This setting is
usually referred to as pixel-level detection. In this paper, we provide a brief
overview of the recent research progress on video anomaly detection and
highlight a few future research directions.
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