Classifying motion in a video using detected visual features
US11836932B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jun 17, 2021 |
| Grant date | Dec 5, 2023 |
| Priority date | — |
| Expiry date | Feb 24, 2042 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/20084
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Technology is disclosed herein for learning motion in video. In an implementation, an artificial neural network extracts features from a video. A correspondence proposal (CP) module performs, for at least some of the features, a search for corresponding features in the video based on a semantic similarity of a given feature to others of the features. The CP module then generates a joint semantic vector for each of the features based at least on the semantic similarity of the given feature to one or more of the corresponding features and a spatiotemporal distance of the given feature to the one or more of the corresponding features. The artificial neural network is able to identify motion in the video using the joint semantic vectors generated for the features extracted from the video.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.