US 11,854,237 B2
Human body identification method, electronic device and storage medium
Zipeng Lu, Beijing (CN); Jian Wang, Beijing (CN); Yuchen Yuan, Beijing (CN); Hao Sun, Beijing (CN); and Errui Ding, Beijing (CN)
Assigned to Beijing Baidu Netcom Science and Technology Co., LTD, Beijing (CN)
Filed by Beijing Baidu Netcom Science and Technology Co., LTD, Beijing (CN)
Filed on Jun. 21, 2021, as Appl. No. 17/353,324.
Claims priority of application No. 202011448336.6 (CN), filed on Dec. 11, 2020.
Prior Publication US 2021/0312172 A1, Oct. 7, 2021
Int. Cl. G06V 10/25 (2022.01); G06V 40/10 (2022.01); G06F 18/214 (2023.01); G06V 10/75 (2022.01); G06V 10/764 (2022.01); G06V 10/774 (2022.01); G06V 10/82 (2022.01)
CPC G06V 10/25 (2022.01) [G06F 18/214 (2023.01); G06V 10/757 (2022.01); G06V 10/764 (2022.01); G06V 10/774 (2022.01); G06V 10/82 (2022.01); G06V 40/10 (2022.01); G06V 40/103 (2022.01)] 15 Claims
OG exemplary drawing
 
1. A human body identification method, comprising:
inputting an image to be identified into a human body detection model, to obtain a plurality of preselected detection boxes;
identifying a plurality of key points from each of the preselected detection boxes respectively according to a human body key point detection model, and obtaining a key point score of each of the key points;
determining a target detection box from each of the preselected detection boxes, according to a number of the key points whose key point scores meet a key point threshold; and
inputting the target detection box into a human body key point classification model, to obtain a human body identification result for the image to be identified,
wherein the key point threshold comprises a low keypoint threshold, and the determining the target detection box from each of the preselected detection boxes, according to the number of the key points whose key point scores meet the key point threshold, comprises:
determining a corresponding preselected detection box as the target detection box, in a case where a first key point number is larger than a preset number, wherein the first key point number is a number of the key points whose key point scores are larger than a low key point threshold,
wherein the key point threshold further comprises a high key point threshold, and the method further comprises:
determining the corresponding preselected detection box as a second high confidence detection box, in a case where the first key point number is greater than zero and less than or equal to the preset number, and a second key point number is greater than or equal to a preset proportion of the first key point number, wherein the second key point number is a number of the key points whose key point scores are lager than the high key point threshold; and
extracting a second human body image area from the image to be identified, according to a size and a position of the second high confidence detection box.