US 12,394,250 B2
Movement extraction method and apparatus for dance video, computer device, and storage medium
Shichen Zhao, Shanghai (CN); Weijia Li, Shanghai (CN); Chaoran Li, Shanghai (CN); Peng Wang, Shanghai (CN); and Zhihui Chen, Shanghai (CN)
Assigned to SHANGHAI BILIBILI TECHNOLOGY CO., LTD., Shanghai (CN)
Appl. No. 18/018,879
Filed by SHANGHAI BILIBILI TECHNOLOGY CO., LTD., Shanghai (CN)
PCT Filed Jun. 22, 2021, PCT No. PCT/CN2021/101384
§ 371(c)(1), (2) Date Jan. 31, 2023,
PCT Pub. No. WO2022/028136, PCT Pub. Date Feb. 10, 2022.
Claims priority of application No. 202010784431.7 (CN), filed on Aug. 6, 2020.
Prior Publication US 2023/0306787 A1, Sep. 28, 2023
Int. Cl. G06V 40/20 (2022.01); G06F 18/23 (2023.01); G06T 7/246 (2017.01); G06V 10/762 (2022.01); G06V 20/40 (2022.01); A63F 13/65 (2014.01); A63F 13/816 (2014.01)
CPC G06V 40/23 (2022.01) [G06F 18/23 (2023.01); G06T 7/248 (2017.01); G06V 10/762 (2022.01); G06V 20/41 (2022.01); A63F 13/65 (2014.09); A63F 13/816 (2014.09); A63F 2300/6607 (2013.01); G06T 2207/10016 (2013.01); G06T 2207/30196 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method of extracting movements from a dance video, comprising:
receiving a dance video that comprises one or more dancers and that is uploaded by a user, and obtaining video frames in the dance video;
recognizing, based on a skeleton node recognition algorithm, skeleton node images from the video frames corresponding to each target dancer selected from the one or more dancers in the dance video, each of the skeleton node images is associated with an identification number, and identification numbers of the skeleton node images indicate a chronological order of video frames in the dance video from which the skeleton node images are generated;
performing cluster analysis on the skeleton node images recognized from the dance video and corresponding to each target dancer to obtain a plurality of cluster sets, wherein the performing cluster analysis on the skeleton node images corresponding to each target dancer to obtain a plurality of cluster sets comprises:
selecting K target skeleton node images from all the skeleton node images,
calculating similarities between each of remaining skeleton node images and the target skeleton node images,
grouping each of the remaining skeleton node images and a corresponding target skeleton node image based on the calculated similarities to obtain K candidate sets,
determining a new target skeleton node image based on identification numbers of skeleton node images comprised in each of the K candidate sets,
repeating calculation of similarities based on K new target skeleton node images and obtaining K new candidate sets, and
in response to determining that identification numbers of K new target skeleton node images no longer change or a preset number of repetitions is reached, identifying K new candidate sets corresponding to the K new target skeleton node images as the plurality of cluster sets;
determining a cluster center in each of the plurality of cluster sets as a key skeleton node image; and
sequentially outputting key skeleton node images to obtain a standard movement sequence corresponding to each target dancer in the dance video.