Patent ID: 11908222
Assignee: HANGZHOU DIANZI UNIVERSITY
Field: Computer technology (Electrical engineering)
Classification: CPC G  Y | IPC G

Claim 4:
5. The method according to claim 4, wherein the specific implementation process of step(2) comprises steps of step 2-1 to step 2-2:
step 2-1: extracting the key-points of the pedestrian images by ViTPose which is pre-trained on the CoCo dataset, and the heat map of the pedestrian key-points ƒpos and key-point set Vkc={V1, V2, . . . , VS} in the pedestrian images are obtained by ViTPose, among which, VS is the key-point of the human body obtained by the pedestrian key-point algorithm, as shown in equation(7):

ƒpos,Vkc=ViTPose(Image)  (7)

wherein VS={kx, ky, kc},kx, ky are the coordinates of key-points respectively, and kc is the key-point confidence; ƒpos is the heat map of key-points output by ViTPose
step 2-2: obtaining S local features of pedestrian key-points by using the local feature map ƒlocal and the heat map ƒpos according to vector outer producting and global average pooling, as shown in equation (8):

ƒkeypoints=GAP(ƒlocal⊗ƒpos)  (8)

wherein GAP is the global average pooling; the group of features of pedestrian key-points ƒkeypoints ∈ RS×C S is the number of key-points and C is the number of feature channels.