Microsoft Corporation
Grouping a first set of video items to efficiently match against a second set of video items using embedding similarity

Last updated:

Abstract:

Techniques for efficiently matching two sets of video items are provided. In on technique, an embedding is generated for each video item in each set. For the first set of video items, multiple groups are generated. The first set of video items may have a relatively little amount of metadata information for them. Each video item in the first set is assigned to one of the groups. Then, for each video item in the second set, one of the groups is selected based on embedding similarity. For each video item in the selected group, an embedding similarity is determined between that video item in the selected group and the video item in the second set. If the embedding similarity is above a certain threshold, then an association is generated for that pair of video items.

Status:
Grant
Type:

Utility

Filling date:

1 Mar 2021

Issue date:

19 Apr 2022