公开(公告)号：US20230360355A1

公开(公告)日：2023-11-09

申请号：US17662050

申请日：2022-05-04

Applicant: MOTOROLA SOLUTIONS, INC.

Inventor： Peter L. Venetianer ,  Burak Kakillioglu ,  Aleksey Lipchin ,  Xiao Xiao

IPC: G06V10/20 ,  G06V20/52 ,  G06T7/194 ,  G06V10/82

CPC classification number: G06V10/255 ,  G06V20/52 ,  G06T7/194 ,  G06V10/82

Abstract: One aspect provides a method for object detection including detecting, using an electronic processor, a plurality of candidate objects in a video using a convolutional neural network detection process and a background subtraction detection process and identifying, using the electronic processor, a candidate object from the plurality of candidate objects. The candidate object detected by the background subtraction detection process in a location of the video with no candidate objects detected by the convolutional neural network detection process. The method also includes determining, using the electronic processor, a background subtraction confidence level of the candidate object and categorizing, using the electronic processor, the candidate object as a detected object in the video in response to the background subtraction confidence level satisfying a background subtraction confidence threshold.

公开(公告)号：US12254659B2

公开(公告)日：2025-03-18

申请号：US17662050

申请日：2022-05-04

Applicant: MOTOROLA SOLUTIONS, INC.

Inventor： Peter L. Venetianer ,  Burak Kakillioglu ,  Aleksey Lipchin ,  Xiao Xiao

IPC: G06V10/20 ,  G06T7/194 ,  G06V10/82 ,  G06V20/52

Abstract: One aspect provides a method for object detection including detecting, using an electronic processor, a plurality of candidate objects in a video using a convolutional neural network detection process and a background subtraction detection process and identifying, using the electronic processor, a candidate object from the plurality of candidate objects. The candidate object detected by the background subtraction detection process in a location of the video with no candidate objects detected by the convolutional neural network detection process. The method also includes determining, using the electronic processor, a background subtraction confidence level of the candidate object and categorizing, using the electronic processor, the candidate object as a detected object in the video in response to the background subtraction confidence level satisfying a background subtraction confidence threshold.