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Configurable Spatial-Temporal Hierarchical Analysis for Flexible Video Anomaly Detection. (arXiv:2305.07328v1 [cs.CV])
cs.CV updates on arXiv.org arxiv.org
Video anomaly detection (VAD) is a vital task with great practical
applications in industrial surveillance, security system, and traffic control.
Unlike previous unsupervised VAD methods that adopt a fixed structure to learn
normality without considering different detection demands, we design a
spatial-temporal hierarchical architecture (STHA) as a configurable
architecture to flexibly detect different degrees of anomaly. The comprehensive
structure of the STHA is delineated into a tripartite hierarchy, encompassing
the following tiers: the stream level, the stack level, and the …
analysis anomaly anomaly detection applications architecture arxiv control design detection hierarchical industrial learn normality practical security surveillance temporal traffic unsupervised video