Real-time single-view action recognition based on key pose analysis for sports videos
First Claim
1. A computer-implemented method for action recognition in a sports video, the method comprising:
- receiving a plurality of training videos, each of the training videos associated with a sports type, and each of the training videos including a plurality of video frames;
training, for each sports type of a plurality of different sports types, one or more feature models using the plurality of the training videos, the training comprising;
training a player detector for detecting location of a player in each video frame of a training video;
training a set of key pose identifiers for a sports action distinctively associated with each sports type of the sports videos, the sports action associated with each sports type of the sports videos being represented by a set of distinctive poses; and
training a meta classifier for determining a likelihood that the sports action has happened in a training video based on identification result by the trained set of key pose identifiers;
selecting one or more trained feature models that are associated with a sports type of an input video; and
applying the selected trained feature models to a plurality of video frames of the input video to recognize a sports action captured by the input video.
3 Assignments
0 Petitions
Accused Products
Abstract
A system is provided for real-time single-view action recognition for sports videos based on key pose analysis of the sports videos. A training module of the system trains feature models for a sports action distinctively associated with each sports type using a large corpus of training videos. The trained feature models include a player detector for detecting locations of a player in video frames of a training video, a set of key pose identifiers for identifying distinctive poses of a sports action associated with a type of sports, and a meta classifier for determining a likelihood that the sports action has happened in a sports video based on the key poses analysis. Responsive to an input sports video being received for real-time action recognition, a set of trained feature models associated with the sports type of the input video are selected and applied to the input video.
80 Citations
20 Claims
-
1. A computer-implemented method for action recognition in a sports video, the method comprising:
-
receiving a plurality of training videos, each of the training videos associated with a sports type, and each of the training videos including a plurality of video frames; training, for each sports type of a plurality of different sports types, one or more feature models using the plurality of the training videos, the training comprising; training a player detector for detecting location of a player in each video frame of a training video; training a set of key pose identifiers for a sports action distinctively associated with each sports type of the sports videos, the sports action associated with each sports type of the sports videos being represented by a set of distinctive poses; and training a meta classifier for determining a likelihood that the sports action has happened in a training video based on identification result by the trained set of key pose identifiers; selecting one or more trained feature models that are associated with a sports type of an input video; and applying the selected trained feature models to a plurality of video frames of the input video to recognize a sports action captured by the input video. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
-
-
11. A non-transitory computer readable storage medium storing computer program instructions, the computer program instructions when executed by a computer processor causes the processor to perform the steps of:
-
receiving a plurality of training videos, each of the training videos associated with a sports type, and each of the training videos including a plurality of video frames; training, for each sports type of a plurality of different sports types, one or more feature models using the plurality of the training videos, the training comprising; training a player detector for detecting location of a player in each video frame of a training video; training a set of key pose identifiers for a sports action distinctively associated with each sports type of the sports videos, the sports action associated with each sports type of the sports videos being represented by a set of distinctive poses; and training a meta classifier for determining a likelihood that the sports action has happened in a training video based on identification result by the trained set of key pose identifiers; selecting one or more trained feature models that are associated with a sports type of an input video; and applying the selected trained feature models to a plurality of video frames of the input video to recognize a sports action captured by the input video. - View Dependent Claims (12, 13, 14, 15, 16, 17, 18, 19, 20)
-
Specification