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Point Cloud Video Anomaly Detection Based on Point Spatio-Temporal Auto-Encoder

Video anomaly detection has great potential in enhancing safety in the production and monitoring of crucial areas. Currently, most video anomaly detection methods are based on RGB modality, but its redundant semantic information may breach the privacy of residents or patients. The 3D data obtained by depth camera and LiDAR can accurately locate anomalous events in 3D space while preserving human posture and motion information.

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Cite this as

Tengjiao He, Wenguang Wang (2024). Dataset: Point Cloud Video Anomaly Detection Based on Point Spatio-Temporal Auto-Encoder. https://doi.org/10.57702/6qe22hjy

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Additional Info

Field	Value
Created	December 16, 2024
Last update	December 16, 2024
Defined In	https://doi.org/10.48550/arXiv.2306.04466
Author	Tengjiao He
More Authors	Wenguang Wang
Homepage	https://arxiv.org/abs/2205.13713