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Unusual Event Detection.pdf

jaeger_08_weakly.pdf
Preview of Unusual Event Detection
🔗 Source: hci.iwr.uni-heidelberg.de
📊 Size: 295 KB
📄 Pages: 23 pages
⬇️ Downloads: 145

Summary

The framework reduces the feature space dimension and encodes temporal dynamics using continuous HMMs. It uses a one-class learning approach, where a regular sequence model is trained and then expanded to an error sequence model using outlier detection. The likelihood ratio of the data given the error sequence model and the regular sequence model is used for classification. Experimental results on image sequences from industrial laser welding processes show that the framework can significantly reduce user interaction and detect error events with a low false positive rate.

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Description

The framework reduces the feature space dimension and encodes temporal dynamics using continuous HMMs.

Technical Information

  • File Format: PDF
  • File Size: 295 KB
  • Pages: 23
  • Language: EN
  • Total Downloads: 145
  • Last Updated: 3 hours ago

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This PDF document about Unusual Event Detection provides comprehensive information and guidance. Whether you're a beginner or advanced user, this resource offers valuable insights into Unusual Event Detection.

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