The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Oct. 15, 2019

Filed:

Sep. 13, 2016
Applicant:

Chuanxian Network Technology (Shanghai) Co., Ltd, Beijing, CN;

Inventors:

Tao Wang, Beijing, CN;

Jinjie Ke, Beijing, CN;

Sibin Gu, Beijing, CN;

Baiyu Pan, Beijing, CN;

Ji Wang, Beijing, CN;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
H04N 19/436 (2014.01); H04N 19/513 (2014.01); H04N 19/523 (2014.01); H04N 19/533 (2014.01);
U.S. Cl.
CPC ...
H04N 19/436 (2014.11); H04N 19/513 (2014.11); H04N 19/523 (2014.11); H04N 19/533 (2014.11);
Abstract

The present disclosure relates to a motion compensation matching method and system for video coding. The method comprises: a CPU extracting a current frame image and a reference frame image from a video to be processed and sending the extracted frame images to a GPU; the GPU performing interpolation process at least once on the reference frame image to obtain a plurality of interpolation images; the GPU dividing the current frame image to obtain a plurality of prediction blocks; the GPU, according to each of the prediction blocks, performing block matching search in the reference frame image and each of the interpolation images; according to a result of the block matching search, determining a motion vector of a desired image block of the current frame image. The present disclosure uses GPU to execute large amounts of computation for interpolation and division of the frame images and block matching search, and uses CPU to process a small amount of computation. Since GPU is used to process search, which can be the most complicated and the most energy-consuming part of the coding process, the large-scale concurrency of the graphics card can be sufficiently utilized, and thus the video coding speed can be significantly increased.


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