公开(公告)号：US20230023164A1

公开(公告)日：2023-01-26

申请号：US17938042

申请日：2022-10-04

Applicant: PERCIPIENT.AI INC.

Inventor： Vasudev PARAMESWARAN ,  Atul KANAUJIA ,  Simon CHEN ,  Jerome BERCLAZ ,  Ivan KOVTUN ,  Alison HIGUERA ,  Vidyadayini TALAPADY ,  Derek YOUNG ,  Balan AYYAR ,  Rajendra SHAH ,  Timo PYLVANAINEN

IPC: G06N3/04 ,  G06V10/72 ,  G06V10/774 ,  G06V10/82

Abstract: A computer vision system configured for detection and recognition of objects in video and still imagery in a live or historical setting uses a teacher-student object detector training approach to yield a merged student model capable of detecting all of the classes of objects any of the teacher models is trained to detect. Further, training is simplified by providing an iterative training process wherein a relatively small number of images is labeled manually as initial training data, after which an iterated model cooperates with a machine-assisted labeling process and an active learning process where detector model accuracy improves with each iteration, yielding improved computational efficiency. Further, synthetic data is generated by which an object of interest can be placed in a variety of setting sufficient to permit training of models. A user interface guides the operator in the construction of a custom model capable of detecting a new object.