Automatic sequencing of video playlists based on mood classification of each video and video cluster transitions
US9165255B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Jul 26, 2012 |
| Grant date | Oct 20, 2015 |
| Priority date | — |
| Expiry date | Dec 26, 2033 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04N21/4825
- WIPO fieldAudio-visual technology
- WIPO sectorElectrical engineering
Abstract
A given set of videos are sequenced in an aesthetically pleasing manner using models learned from human curated playlists. Semantic features associated with each video in the curated playlists are identified and a first order Markov chain model is learned from curated playlists. In one method, a directed graph using the Markov model is induced, wherein sequencing is obtained by finding the shortest path through the directed graph. In another method a sampling based approach is implemented to produce paths on the digraph. Multiple samples are generated and the best scoring sample is returned as the output. In a third method, a relevance based random walk sampling algorithm is modified to produce a reordering of the playlist.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.