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» Learning with Local Drift Detection
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CVPR
2009
IEEE
16 years 6 months ago
Observe Locally, Infer Globally: a Space-Time MRF for Detecting Abnormal Activities with Incremental Updates
We propose a space-time Markov Random Field (MRF) model to detect abnormal activities in video. The nodes in the MRF graph correspond to a grid of local regions in the video fra...
Jaechul Kim (University of Texas at Austin), Krist...
KDD
2005
ACM
178views Data Mining» more  KDD 2005»
15 years 5 months ago
Failure detection and localization in component based systems by online tracking
The increasing complexity of today’s systems makes fast and accurate failure detection essential for their use in mission-critical applications. Various monitoring methods provi...
Haifeng Chen, Guofei Jiang, Cristian Ungureanu, Ke...
ICCV
2011
IEEE
13 years 11 months ago
Hough-based Tracking of Non-Rigid Objects
Online learning has shown to be successful in tracking of previously unknown objects. However, most approaches are limited to a bounding-box representation with fixed aspect rati...
Martin Godec, Peter M. Roth, Horst Bischof
IDEAL
2005
Springer
15 years 5 months ago
SOM-Based Novelty Detection Using Novel Data
Novelty detection involves identifying novel patterns. They are not usually available during training. Even if they are, the data quantity imbalance leads to a low classification ...
Hyoungjoo Lee, Sungzoon Cho
VMV
2008
162views Visualization» more  VMV 2008»
15 years 1 months ago
Learning Distinctive Local Object Characteristics for 3D Shape Retrieval
While supervised learning approaches for 3D shape retrieval have been successfully used to incorporate human knowledge about object classes based on global shape features, the inc...
Raoul Wessel, Rafal Baranowski, Reinhard Klein