Methods and systems of spatiotemporal pattern recognition for video content development
First Claim
Patent Images
1. A method for delivering personalized video content, comprising:
- processing at least one video feed through at least one spatiotemporal pattern recognition algorithm that uses machine learning to develop an understanding of at least one event within the at least one video feed of a professional game, wherein the understanding developed by the machine learning includes an entry in a relationship library at least detailing a relationship between two visible features of the at least one video feed;
capturing 3D video of a non-professional player as a data feed;
developing an understanding using the machine learning of at least one event within the data feed relating to motion of the non-professional player; and
automatically, under computer control, providing an enhanced video feed that mixes video of the non-professional player with the at least one video feed of the professional game and represents the nonprofessional player as an animation having attributes based on the data feed relating to motion of the non-professional player playing within a context of the professional game based on the understanding of the at least one event within the at least one video feed of the professional game and the data feed relating to the motion of the non-professional player.
3 Assignments
0 Petitions
Accused Products
Abstract
An enhanced video of an event in a first video feed, which is identified by a spatiotemporal pattern recognition algorithm that uses machine learning for understanding the event, is produced by including in the enhanced video an animation that characterizes a person'"'"'s motions that are derived from a machine learning-based understanding of an event in a second video.
-
Citations
6 Claims
-
1. A method for delivering personalized video content, comprising:
-
processing at least one video feed through at least one spatiotemporal pattern recognition algorithm that uses machine learning to develop an understanding of at least one event within the at least one video feed of a professional game, wherein the understanding developed by the machine learning includes an entry in a relationship library at least detailing a relationship between two visible features of the at least one video feed; capturing 3D video of a non-professional player as a data feed; developing an understanding using the machine learning of at least one event within the data feed relating to motion of the non-professional player; and automatically, under computer control, providing an enhanced video feed that mixes video of the non-professional player with the at least one video feed of the professional game and represents the nonprofessional player as an animation having attributes based on the data feed relating to motion of the non-professional player playing within a context of the professional game based on the understanding of the at least one event within the at least one video feed of the professional game and the data feed relating to the motion of the non-professional player. - View Dependent Claims (2, 3, 4, 5, 6)
-
Specification