US 12,260,333 B2
Semi-supervised person re-identification using multi-view clustering
Jinjun Wang, San Jose, CA (US); and Xiaomeng Xin, Xi'an (CN)
Assigned to DeepNorth Inc., San Carlos, CA (US)
Filed by DeepNorth Inc., Redwood City, CA (US)
Filed on Oct. 18, 2023, as Appl. No. 18/489,401.
Application 18/489,401 is a continuation of application No. 18/078,008, filed on Dec. 8, 2022, granted, now 11,823,050.
Application 18/078,008 is a continuation of application No. 16/164,572, filed on Oct. 18, 2018, granted, now 11,537,817.
Prior Publication US 2024/0046094 A1, Feb. 8, 2024
This patent is subject to a terminal disclaimer.
Int. Cl. G06N 3/045 (2023.01); G06F 18/21 (2023.01); G06F 18/214 (2023.01); G06F 18/23 (2023.01); G06N 3/08 (2023.01); G06V 20/52 (2022.01); G06V 40/10 (2022.01)
CPC G06N 3/08 (2013.01) [G06F 18/2155 (2023.01); G06F 18/217 (2023.01); G06F 18/23 (2023.01); G06N 3/045 (2023.01); G06V 20/52 (2022.01); G06V 40/10 (2022.01)] 26 Claims
OG exemplary drawing
 
1. A computer system, comprising:
a processor; and
system memory coupled to the processor and storing instructions configured to cause the processor to:
initialize a set of person re-identification neural networks on labeled training data;
iteratively tune the set of person re-identification neural networks using unlabeled data along with pseudo labels estimated for the unlabeled data; and
after tuning:
extract human facial features from the unlabeled data set;
perform multi-view clustering on the extracted human facial features estimating additional pseudo labels for the unlabeled data set; and
further tune the set of person re-identification neural networks using the unlabeled data along with the additional pseudo labels.