Anomaly Detection with a Spatio-Temporal Tracking of the Laser Spot

被引：1

作者：

Atienza, David ^{[1
]}

Bielza, Concha ^{[1
]}

Diaz, Javier ^{[1
,2
]}

Larranaga, Pedro ^{[1
]}

机构：

[1] Tech Univ Madrid, Dept Artificial Intelligence, Madrid, Spain

[2] IKERGUNE AIE, Elgoibar, Spain

来源：

PROCEEDINGS OF THE EIGHTH EUROPEAN STARTING AI RESEARCHER SYMPOSIUM (STAIRS 2016) | 2016年 / 284卷

关键词：

Kernel density estimation; Anomaly detection; Time-series; Laser surface heating process;

D O I：

10.3233/978-1-61499-682-8-137

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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, 32x32 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.

引用

页码：137 / 142

页数：6

共 50 条

[21] Spectrum Anomaly Detection Based on Spatio-Temporal Network Prediction
Peng, Chuang
Hu, Weilin
Wang, Lunwen
ELECTRONICS, 2022, 11 (11)
[22] Anomaly Detection with Spatio-Temporal Context Using Depth Images
Ma, Xiaolin
Lu, Tong
Xu, Feiming
Su, Feng
2012 21ST INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION (ICPR 2012), 2012, : 2590 - 2593
[23] Distributed Anomaly Detection Algorithm for Spatio-Temporal Trajectories of Vehicles
Lu, Liping
Cheng, Hao
Xiong, Shengwu
Duan, Pengfei
Xiao, Yuan
2017 15TH IEEE INTERNATIONAL SYMPOSIUM ON PARALLEL AND DISTRIBUTED PROCESSING WITH APPLICATIONS AND 2017 16TH IEEE INTERNATIONAL CONFERENCE ON UBIQUITOUS COMPUTING AND COMMUNICATIONS (ISPA/IUCC 2017), 2017, : 590 - 598
[24] Detecting Regions of Maximal Divergence for Spatio-Temporal Anomaly Detection
Barz, Bjorn
Rodner, Erik
Garcia, Yanira Guanche
Denzler, Joachim
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2019, 41 (05) : 1088 - 1101
[25] Anomaly detection with a moving camera using spatio-temporal codebooks
Nakahata, Mateus T.
Thomaz, Lucas A.
da Silva, Allan F.
da Silva, Eduardo A. B.
Netto, Sergio L.
MULTIDIMENSIONAL SYSTEMS AND SIGNAL PROCESSING, 2018, 29 (03) : 1025 - 1054
[26] Spatio-Temporal Motion Features for Laser-based Moving Objects Detection and Tracking
Shen, Xiaotong
Kim, Seong-Woo
Ang, Marcelo H., Jr.
2014 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS 2014), 2014, : 4253 - 4259
[27] Robust Lane Detection and Tracking with Propagated Spatio-temporal Constraints
Li, Tingting
Li, Kunqian
Tao, Wenbing
PROCEEDINGS 2017 4TH IAPR ASIAN CONFERENCE ON PATTERN RECOGNITION (ACPR), 2017, : 202 - 207
[28] Adaptive background learning for vehicle detection and spatio-temporal tracking
Zhang, CC
Chen, SC
Shyu, ML
Peeta, S
ICICS-PCM 2003, VOLS 1-3, PROCEEDINGS, 2003, : 797 - 801
[29] Normal Spatio-Temporal Information Enhance for Unsupervised Video Anomaly Detection
Wang, Jun
Jia, Di
Huang, Ziqing
Zhang, Miaohui
Ren, Xing
NEURAL PROCESSING LETTERS, 2023, 55 (08) : 10727 - 10745
[30] Anomaly Detection via Local Coordinate Factorization and Spatio-Temporal Pyramid
Xiao, Tan
Zhang, Chao
Zha, Hongbin
Wei, Fangyun
COMPUTER VISION - ACCV 2014, PT V, 2015, 9007 : 66 - 82

← 1 2 3 4 5 →