Automatic sequencing of video playlists based on mood classification of each video and video cluster transitions
- Applicant
- Auteurs
- N/A
- Titre
- Automatic sequencing of video playlists based on mood classification of each video and video cluster transitions
- Patent Number
- US9165255
- Publication Date
- 2015
- uri
- https://patents.google.com/patent/US9165255
- Description
- 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.
- keywords
- Mood
- Domaine de recherche
- Sentiment Analysis
- Social Media and User Engagement
- Software Development
- Données collectées (type source)
- Audio
- Video
- Concepts clés
- Musical Mood
- Méthode
- Mood descriptors are extracted from adjectives associated with curated and uncurated playlists in a video repository. A classifier is trained from these mood descriptors to generate dimensional mood features for each video in the curated playlists.
- Dispositif
- Device
- Objectifs du brevet
- Determine/Identify Content Emotion
- Pages du site
- Contenu
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