Classifier anomalies for observed behaviors in a video surveillance system
US8180105B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Sep 17, 2009 |
| Grant date | May 15, 2012 |
| Priority date | — |
| Expiry date | Nov 18, 2030 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V20/52
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Techniques are disclosed for a video surveillance system to learn to recognize complex behaviors by analyzing pixel data using alternating layers of clustering and sequencing. A combination of a self organizing map (SOM) and an adaptive resonance theory (ART) network may be used to identify a variety of different anomalous inputs at each cluster layer. As progressively higher layers of the cortex model component represent progressively higher levels of abstraction, anomalies occurring in the higher levels of the cortex model represent observations of behavioral anomalies corresponding to progressively complex patterns of behavior.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.