公开(公告)号：US20230118532A1

公开(公告)日：2023-04-20

申请号：US17954354

申请日：2022-09-28

Applicant: Axis AB

Inventor： Björn BENDERIUS ,  Jimmie JÖNSSON ,  Johan Jeppsson KARLIN ,  Niclas SVENSSON ,  Andreas MUHRBECK

IPC: G06V40/40 ,  G06V40/16 ,  G06V10/82 ,  G06T7/80

Abstract: A first image is captured by the camera, using a first focus setting and a first aperture size. A first protrusion focus measure in a protrusion area of an object in the first image and a first recess focus measure in a recess area of the object in the first image are determined. A second image is captured by the camera, using the first focus setting and a second aperture size, and the object is detected. A second protrusion focus measure and a second recess focus measure are determined in the second image. A protrusion focus difference between the first and second protrusion focus measures, and a recess focus difference between the first and second recess focus measures are calculated. The protrusion focus difference and the recess focus difference are compared and if they differ by less than a predetermined threshold amount, it is determined that the object is fake.

公开(公告)号：US20210350129A1

公开(公告)日：2021-11-11

申请号：US17224610

申请日：2021-04-07

Applicant: Axis AB

Inventor： Andreas MUHRBECK ,  Anton JAKOBSSON ,  Niclas SVENSSON

IPC: G06K9/00 ,  G06N3/08 ,  G06T7/90

Abstract: Methods and apparatus, including computer program products, for processing images recorded by a camera (202) monitoring a scene (200). A set of images (204, 206, 208) is received. The set of images (204, 206, 208) includes differently exposed images of the scene (200) recorded by the camera (202). The set of images (204, 206, 208) is processed by a trained neural network (210) configured to perform object detection, object classification and/or object recognition in image data, wherein the neural network (210) uses image data from at least two differently exposed images in the set of images (204, 206, 208) to detect objects in the set of images (204, 206, 208).