Semantic representation module of a machine learning engine in a video analysis system
US8923609B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Apr 2, 2013 |
| Grant date | Dec 30, 2014 |
| Priority date | — |
| Expiry date | Apr 2, 2033 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V20/44
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A machine-learning engine is disclosed that is configured to recognize and learn behaviors, as well as to identify and distinguish between normal and abnormal behavior within a scene, by analyzing movements and/or activities (or absence of such) over time. The machine-learning engine may be configured to evaluate a sequence of primitive events and associated kinematic data generated for an object depicted in a sequence of video frames and a related vector representation. The vector representation is generated from a primitive event symbol stream and a phase space symbol stream, and the streams describe actions of the objects depicted in the sequence of video frames.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.