US 12,406,502 B2
Enriched and discriminative convolutional neural network features for pedestrian re-identification and trajectory modeling
Kok Yiu Wong, Hong Kong (CN); and Jack Chin Pang Cheng, Hong Kong (CN)
Assigned to The Hong Kong University of Science and Technology, Hong Kong (CN)
Filed by The Hong Kong University of Science and Technoloy, Hong Kong (CN)
Filed on Jul. 26, 2022, as Appl. No. 17/873,462.
Claims priority of provisional application 63/249,025, filed on Sep. 28, 2021.
Prior Publication US 2023/0095533 A1, Mar. 30, 2023
Int. Cl. G06V 20/52 (2022.01); G06T 7/292 (2017.01); G06V 10/46 (2022.01); G06V 10/74 (2022.01); G06V 10/762 (2022.01)
CPC G06V 20/52 (2022.01) [G06T 7/292 (2017.01); G06V 10/46 (2022.01); G06V 10/761 (2022.01); G06V 10/762 (2022.01)] 20 Claims
OG exemplary drawing
 
1. A method for image processing, comprising:
obtaining, by a processing system, data from a plurality of cameras, the data comprising multiple images associated with one or more objects;
extracting, by the processing system, features for each of the multiple images;
determining, by the processing system, a descriptor for each of the multiple images, wherein a respective descriptor for a respective image comprises a first set of units representing all the extracted features in the respective image and a second set of units representing a subset of the extracted features in the respective image, wherein the respective descriptor is represented by a vector comprising a plurality of elements, and wherein each element corresponds to a feature among all the extracted features;
grouping, by the processing system, the descriptors into a number of clusters based on similarities between the descriptors;
determining, by the processing system, an aggregated descriptor for each cluster of the number of clusters, wherein determining the aggregated descriptor for each cluster further comprises determining a mean value for each element in the aggregated descriptor based on corresponding elements in descriptors in a cluster; and
identifying, by the processing system, based on the aggregated descriptors for the number of clusters, one or more images among the multiple images associated with an object among the one or more objects.