TRASMIL: A local anomaly detection framework based on trajectory segmentation and multi-instance learning

Academic Press Inc Elsevier Science
Publication Type:
Journal Article
Computer Vision And Image Understanding, 2013, 117 (10), pp. 1273 - 1286
Issue Date:
Full metadata record
Files in This Item:
Filename Description Size
Thumbnail2013001024OK.pdf2.04 MB
Adobe PDF
Local anomaly detection refers to detecting small anomalies or outliers that exist in some subsegments of events or behaviors. Such local anomalies are easily overlooked by most of the existing approaches since they are designed for detecting global or l
Please use this identifier to cite or link to this item: