Abstract: A method of learning a target object by detecting an edge from a digital model of the target object and setting a sample point according to one embodiment of the present disclosure, which is performed by a computer-aided design program of an authoring computing device, includes: displaying a digital model of a target object that is a target of image recognition; detecting edges on the digital model of the target object; classifying the detected edges according to a plurality of characteristics; obtaining sample point information on the detected edges; and generating object recognition library data for recognizing a real object implementing the digital model of the target object based on the detected edges, characteristic information of the detected edges, and the sample point information.

Abstract: Provided is a method of learning a target object implemented on a computer-aided design program of an authoring computing device using a virtual viewpoint camera, including displaying a digital model of a target object that is a target for image recognition, setting at least one observation area surrounding the digital model of the target object and having a plurality of viewpoints on the digital model, generating a plurality of pieces of image data obtained by viewing the digital model of the target object at the plurality of viewpoints of the at least one observation area, and generating object recognition library data for recognizing a real object implementing the digital model of the target object based on the generated plurality of pieces of image data.

Abstract: The present disclosure provides a method for recognizing 2D code information.

Abstract: The present disclosure provides a method for recognizing 2D code information.

Abstract: In a method for learning a target object, performed by a computer-aided design program of an authoring computing device, one embodiment of the present disclosure provides a method for learning a target object by extracting edges from a digital model of a target object, where the method comprises displaying the digital model of a target object which is an image recognition target, extracting a first edge with visibility greater than or equal to a threshold from a first area of the digital model of the target object, detecting a second edge with visibility greater than or equal to a threshold from a second area different from the first area of the digital model of the target object, and generating object recognition library data for recognizing a real object corresponding to the digital model of the target object based on the first and second edges.

Abstract: A method of tracking a CAD model in real time based on a particle filter according to one embodiment of the present disclosure is a method of detecting and tracking a real object based on target object recognition data for a digital model designed on CAD executed by a CAD object tracking detection program installed in a user computing device. The method includes: acquiring an image captured by photographing a surrounding object; detecting a real object corresponding to a shape of a target object designed in CAD from a first frame image of the captured image; and tracking the detected real object in a second frame image of the captured image, wherein the tracking of the detected real object includes determining a new pose of the real object in the second frame image based on the particle filter with respect to an initial pose of the detected real object.

Abstract: Provided is a method of learning a target object implemented on a computer-aided design program of an authoring computing device using a virtual viewpoint camera, including displaying a digital model of a target object that is a target for image recognition, setting at least one observation area surrounding the digital model of the target object and having a plurality of viewpoints on the digital model, generating a plurality of pieces of image data obtained by viewing the digital model of the target object at the plurality of viewpoints of the at least one observation area, and generating object recognition library data for recognizing a real object implementing the digital model of the target object based on the generated plurality of pieces of image data.

Abstract: A method of learning a target object by detecting an edge from a digital model of the target object and setting a sample point according to one embodiment of the present disclosure, which is performed by a computer-aided design program of an authoring computing device, includes: displaying a digital model of a target object that is a target of image recognition; detecting edges on the digital model of the target object; classifying the detected edges according to a plurality of characteristics; obtaining sample point information on the detected edges; and generating object recognition library data for recognizing a real object implementing the digital model of the target object based on the detected edges, characteristic information of the detected edges, and the sample point information.