Querying video data with reduced latency and cost
US10685235B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | May 4, 2018 |
| Grant date | Jun 16, 2020 |
| Priority date | — |
| Expiry date | Aug 24, 2038 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V20/41
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method can include classifying, using a compressed and specialized convolutional neural network (CNN), an object of a video frame into classes, clustering the object based on a distance of a feature vector of the object to a feature vector of a centroid object of the cluster, storing top-k classes, a centroid identification, and a cluster identification, in response to receiving a query for objects of class X from a specific video stream, retrieving image data for each centroid of each cluster that includes the class X as one of the top-k classes, classifying, using a ground truth CNN (GT-CNN), the retrieved image data for each centroid, and for each centroid determined to be classified as a member of the class X providing image data for each object in each cluster associated with the centroid.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.