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Synchronization of image data from multiple three-dimensional cameras for image recognition

  • US 10,467,454 B2
  • Filed: 04/26/2017
  • Issued: 11/05/2019
  • Est. Priority Date: 04/26/2017
  • Status: Active Grant
First Claim
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1. A method comprising, during an active session:

  • capturing, by a plurality of three-dimensional (3D) cameras in a top section of a checkout apparatus, 3D images of a region over a surface of a base in the checkout apparatus, the surface comprising a pattern, and wherein the checkout apparatus comprises a post section connecting the base to the top section in a spaced relationship, each 3D camera from the plurality of 3D cameras defining a camera coordinate system, each 3D image comprising pixel data having three coordinates in the camera coordinate system, wherein the 3D images comprise 3D pixel object data of an object on the surface and the pattern;

    for each 3D camera, analyzing, by one or more processors, the 3D image to determine a location of the pattern relative to the respective 3D camera, wherein the pattern is indicates a common 3D coordinate system shared by the 3D cameras;

    for each 3D camera, calibrating the respective 3D camera during the active session, comprising determining a coordinate transformation function to convert pixel data in the 3D image from the camera coordinate system of the 3D camera to the common 3D coordinate system shared by the 3D cameras, the coordinate transformation function being determined based on the identified location of the pattern in the respective 3D image and the common 3D coordinate system;

    for the captured 3D images, transforming, by the one or more processors, the 3D pixel object data to the common 3D coordinate system, using the coordinate transformation function, to obtain transformed 3D pixel object data, wherein the transformed 3D pixel object data for the plurality of 3D cameras is defined for the same common 3D coordinate system;

    combining, by the one or more processors, the transformed 3D pixel object data from the captured 3D images to obtain a composite 3D pixel object data for the object; and

    performing, by the one or more processors, object recognition of the object on the surface based on an appearance of the object described in the composite 3D pixel object data.

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