US 11,955,143 B2
Automatic video editing method and portable terminal
Wenjie Jiang, Shenzhen (CN); Jinlin Cai, Shenzhen (CN); and Jingkang Liu, Shenzhen (CN)
Assigned to ARASHI VISION INC., Guangdong (CN)
Appl. No. 17/432,411
Filed by ARASHI VISION INC., Guangdong (CN)
PCT Filed Apr. 22, 2020, PCT No. PCT/CN2020/086188
§ 371(c)(1), (2) Date Aug. 19, 2021,
PCT Pub. No. WO2020/169121, PCT Pub. Date Aug. 27, 2020.
Claims priority of application No. 201910132043.8 (CN), filed on Feb. 22, 2019.
Prior Publication US 2022/0199121 A1, Jun. 23, 2022
Int. Cl. G11B 27/036 (2006.01); G06V 10/98 (2022.01); G06V 20/40 (2022.01); G11B 27/34 (2006.01)
CPC G11B 27/036 (2013.01) [G06V 10/993 (2022.01); G06V 20/41 (2022.01); G06V 20/46 (2022.01); G06V 20/49 (2022.01); G11B 27/34 (2013.01); G06V 2201/07 (2022.01)] 16 Claims
OG exemplary drawing
 
1. An automatic video editing method, comprising:
acquiring a video to be edited;
extracting a key frame of the video to be edited;
inputting the key frame into a pre-trained scene categorization method and a pre-trained target detection method to respectively obtain a marker of a scene type and a marker of a target object;
screening out a plurality of video segments meeting a preset editing rule from the video to be edited;
respectively calculating an average score of the plurality of video segments through a pre-trained image quality scoring method;
acquiring and stitching video segments with a highest average score corresponding to each lens type;
wherein the inputting the key frame into a pre-trained scene categorization method and a pre-trained target detection method to respectively obtain a marker of a scene type and a marker of a target object comprises:
there being p scene types in the pre-trained scene categorization method, p corresponding to a sequence of preset scene types, with p≥100, inputting the i-th key frame into the pre-trained scene categorization method to determine the scene type of the key frame, obtaining the marker Si of the scene type, with Si∈[0, p];
there being k preset target objects, k corresponding to a sequence of preset target objects, with k≥50, inputting the i-th key frame into the pre-trained target detection method to detect the target object in the key frame, and obtaining the marker Di of the target object, with Di∈[0, k].