National Yang Ming Chiao Tung University

Wen-Hsiao Peng

Yi-Wen Chen

Chun-Chi Chen

Hsueh-Ming Hang

Yung-Han Ho

Yun Liang

Guo-Lun Jin

Ru-Ling Liao

A reinforcement learning method for frame-level bit allocation is disclosed. The reinforcement learning method includes steps of: (a) at a testing time, computing a state according to a plurality of features; (b) determining an action according to a policy; (c) determining a number of bits allocated to an i-th frame in a group of pictures (GOP) according to the action, a GOP-level bit budget and the state, wherein i is a positive integer; (d) encoding the i-th frame according to the number of bits allocated to the i-th frame in the GOP; and (e) repeating the steps (a)&#x2dc;(d) until an end of the GOP.

Reinforcement learning method for video encoder

A video encoding method is provided in the invention. In such method, after a current encoding frame among a sequence of input frames is received, each coding unit in the current encoding frame may be optionally split into two oblong prediction units, and each of the prediction units may be optionally split into a plurality of sub-blocks so as to thereby improve the matching accuracy for a matching reference block from a reference frame. A video decoding method corresponding to the aforesaid video encoding method is also provided.

Method for encoding/decoding video by oblong intra prediction

A frame prediction system and a prediction method thereof. An initializing module initializes a first image block having a plurality of pixels. A providing module provides a first centroid and a first motion vector of a second image block. The location lookup module finds a location according to the first centroid, and generates a first weight and a second weight respectively according to a relationship between each of the pixels, the first centroid and the location. A vector lookup module finds a second motion vector, which gives a minimum pixel intensity error for the plurality of pixels in the first image block according to the first centroid, the first motion vector, the location, the first weight and the second weight. A processing module sequentially calculates a plurality of predictive intensity values according to the motion vectors and the weights.

Frame prediction system and prediction method thereof

Growing community of inventors

Hsinchu County, Taiwan

Wen-Hsiao Peng