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Anomaly detection with a spatio-temporal tracking of the laser spot
Citation
Atienza González, David, Bielza Lozoya, María Concepción 
ORCID: https://orcid.org/0000-0001-7109-2668, Díaz Rozo, Javier and Larrañaga Múgica, Pedro María ORCID: https://orcid.org/0000-0002-1885-4501
(2016).
Anomaly detection with a spatio-temporal tracking of the laser spot.
In: "Eighth European Starting AI Researcher Symposium", 26 Aug - 02 Sep 2016, La Haya, Holanda. ISBN 978-1-61499-681-1. pp. 137-142.
https://doi.org/10.3233/978-1-61499-682-8-137.
Description
| Title: | Anomaly detection with a spatio-temporal tracking of the laser spot |
|---|---|
| Author/s: |
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| Item Type: | Presentation at Congress or Conference (Article) |
| Event Title: | Eighth European Starting AI Researcher Symposium |
| Event Dates: | 26 Aug - 02 Sep 2016 |
| Event Location: | La Haya, Holanda |
| Title of Book: | Stairs 2016: Proceedings of the Eighth European Starting Ai Researcher Symposium |
| Date: | 2016 |
| ISBN: | 978-1-61499-681-1 |
| Volume: | 284 |
| Subjects: | |
| Freetext Keywords: | Kernel density estimation; Anomaly detection; Time-series; Laser surface heating process |
| Faculty: | E.T.S. de Ingenieros Informáticos (UPM) |
| Department: | Inteligencia Artificial |
| Creative Commons Licenses: | Recognition - No derivative works - Non commercial |
Abstract
Anomaly detection is an important problem with many applications in industry. This paper introduces a new methodology for detecting anomalies in a real laser heating surface process recorded with a high-speed thermal camera (1000 fps, 32×32 pixels). The system is trained with non-anomalous data only (32 videos with 21500 frames). The proposed method is built upon kernel density estimation and is capable of detecting anomalies in time-series data. The classification should be completed in-process, that is, within the cycle time of the workpiece.
More information
| Item ID: | 46642 |
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| DC Identifier: | https://oa.upm.es/46642/ |
| OAI Identifier: | oai:oa.upm.es:46642 |
| DOI: | 10.3233/978-1-61499-682-8-137 |
| Official URL: | http://ebooks.iospress.nl/volumearticle/45049 |
| Deposited by: | Memoria Investigacion |
| Deposited on: | 18 Oct 2017 10:08 |
| Last Modified: | 11 Jan 2023 08:43 |
