Abnormal behavior detection system and method using automatic classification of multiple features
US8885929B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Nov 29, 2010 |
| Grant date | Nov 11, 2014 |
| Priority date | — |
| Expiry date | Jun 19, 2031 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG08G1/0175
- WIPO fieldControl
- WIPO sectorInstruments
Abstract
Described herein are a system and a method for abnormal behavior detection using automatic classification of multiple features. Features from various sources, including those extracted from camera input through digital image analysis, are used as input to machine learning algorithms. These algorithms group the features and produce models of normal and abnormal behaviors. Outlying behaviors, such as those identified by their lower frequency, are deemed abnormal. Human supervision may optionally be employed to ensure the accuracy of the models. Once created, these models can be used to automatically classify features as normal or abnormal. This invention is suitable for use in the automatic detection of abnormal traffic behavior such as running of red lights, driving in the wrong lane, or driving against traffic regulations.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.