Surveillance system using deep network flow for multi-object tracking
US10402983B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Sep 5, 2017 |
| Grant date | Sep 3, 2019 |
| Priority date | — |
| Expiry date | Dec 14, 2037 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/30241
- WIPO fieldAudio-visual technology
- WIPO sectorElectrical engineering
Abstract
A surveillance system and method are provided. The surveillance system includes at least one camera configured to capture a set of images of a given target area that includes a set of objects to be tracked. The surveillance system includes a memory storing a learning model configured to perform multi-object tracking by jointly learning arbitrarily parameterized and differentiable cost functions for all variables in a linear program that associates object detections with bounding boxes to form trajectories. The surveillance system includes a processor configured to perform surveillance of the target area to (i) detect the objects and track locations of the objects by applying the learning model to the images in a surveillance task that uses the multi-object tracking, and (ii), provide a listing of the objects and their locations for surveillance task. A bi-level optimization is used to minimize a loss defined on a solution of the linear program.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.