Trajectory Clustering-Based Anomaly Detection in Indoor Human Movement

Trajectory Clustering-Based Anomaly Detection in Indoor Human Movement

Human movement anomalies in indoor spaces commonly involve urgent situations, such as security threats, accidents, and fires. This paper proposes a two-phase framework for detecting indoor human trajectory anomalies based on density-based spatial clustering of applications with noise (DBSCAN). The f...

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Bibliographic Details
Main Authors: Doi Thi Lan, Seokhoon Yoon
Format: Article
Language:English
Published: MDPI AG 2023-03-01
Series:Sensors
Subjects:
anomaly detection
indoor human trajectory
DBSCAN
cluster validity index
epsilon parameter
similarity measurement
Online Access:https://www.mdpi.com/1424-8220/23/6/3318

Internet

https://www.mdpi.com/1424-8220/23/6/3318

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