Apparatus and method for prediction of video frame based on deep learning

A method of predicting a video frame, the method comprising:

• extracting at least one feature from a video frame;
• obtaining predicted feature data trained based on the at least one feature or corresponding to the at least one feature;
• and
• obtaining a predicted video frame based on the predicted feature data,
• wherein the extracting of the at least one feature from the video frame includes:
• receiving first to (T−1)th video frames, respectively, and extracting at least one feature from each of the first to (T−1)th video frames, where “T” includes a natural number of 2 or more,
• wherein the training based on the at least one feature includes:
• training based on at least one feature extracted from each of the first to (T−1)th video frames,
• wherein the extracting of the at least one feature from the video frame includes:
• receiving a T-th video frame and extracting at least one feature from the T-th video frame,
• wherein the obtaining of the predicted video frame based on the predicted feature data includes:
• obtaining a (T+1) th predicted video frame corresponding to the T th video frame based on the predicted feature data.

A method of predicting a video frame, the method comprising:

• extracting at least one feature from a video frame;
• obtaining predicted feature data trained based on the at least one feature or corresponding to the at least one feature;
• and
• obtaining a predicted video frame based on the predicted feature data,
• wherein the extracting of the at least one feature from the video frame includes:
• receiving first to (T−1)th video frames, respectively, and extracting at least one feature from each of the first to (T−1)th video frames, where “T” includes a natural number of 2 or more, and
• wherein the training based on the at least one feature includes:
• training based on at least one feature extracted from each of the first to (T−1)th video frames,
• wherein the extracting of the at least one feature from the video frame includes:
• extracting, by the first-level encoder to the N-th level encoder, features of different levels from each other from the video frame, where “N” includes a natural number equal to or greater than 2,
• wherein the obtaining of the predicted feature data corresponding to the at least one feature includes:
• receiving, by a first feature learning unit to an N-th feature learning unit corresponding to the first-level encoder to the N-th level encoder, the features of the different levels, respectively;
• and
• obtaining, by the first feature learning unit to the N-th feature learning unit, the predicted feature data corresponding to each of the features of the different levels, respectively, and transmitting the predicted feature data to a next frame processing process, and
• wherein the obtaining of the predicted video frame based on the predicted feature data includes:
• receiving each of the predicted feature data by a first-level decoder to an N-th level decoder, respectively;
• and
• generating, by the first-level decoder to the N-th level decoder, the predicted video frame by using the predicted feature data, and
• wherein the first-level decoder to the N-th level decoder correspond to each of the first-level encoder to the N-th level encoder, or corresponding to each of the first feature learning unit to the N-th feature learning unit.