Codeless anchor generation for three-dimensional object models
A client device that includes a camera and an extended reality client application program is employed by a user in a physical space, such as an industrial or campus environment. The user aims the camera within the mobile device at a real-world asset, such as a computer system, classroom, or vehicle. The client device acquires a digital representation, comprising a 2D representation of a physical space and depth map, and detects 3D objects included in the acquired representation that corresponds to one or more anchors. The client device queries a data intake and query system for asset content associated with the detected anchors. Upon receiving the asset content from the data intake and query system, the client device generates visualizations of the asset content and presents the visualizations via a display device.
1. A computer-implemented method, comprising:
receiving a representation of a physical space that includes a real-world asset;
generating, based on the representation, an object anchor representing the real-world asset, wherein the object anchor includes a reference image of the real-world asset;
identifying asset content that includes data associated with the real-world asset; and
generating an association between the asset content and the object anchor, wherein, based on the association between the asset content and the object anchor, at least a portion of the asset content is configured to be presented in proximity to the real-world asset in an extended-reality (XR) environment in response to determining that a feature of a captured image including the real-world asset matches a feature of the reference image included in the object anchor.
2. The computer-implemented method of claim 1 , wherein the at least a portion of the asset content is configured to be presented at a position in the XR environment based on a position of the object anchor.
3. The computer-implemented method of claim 1 , wherein the representation of the physical space comprises a bounding box drawn in the XR environment via a mobile device.
4. The computer-implemented method of claim 1 , wherein the representation of the physical space comprises a set of meshes corresponding to a real-world environment contained within the representation of the physical space.
5. The computer-implemented method of claim 1 , wherein the representation of the physical space comprises a set of meshes retrieved based on a selection of at least a portion of the physical space within the XR environment.
6. The computer-implemented method of claim 1 , wherein at least a portion of the real-world asset is present in the representation.
7. The computer-implemented method of claim 1 , further comprising mapping a two-dimensional texture image extracted from the representation of the physical space to a three-dimensional object model extracted from the representation of the physical space, wherein the object anchor comprises the two-dimensional texture image and the dimensional object model.
8. The computer-implemented method of claim 1 , wherein generating the association between the asset content and the object anchor comprises:
identifying a set of mesh faces, wherein each mesh face included in the set of mesh faces corresponds to a surface in the physical space;
selecting a subset of mesh faces from among the set of mesh faces, wherein at least a portion of each mesh face included in the subset of mesh faces is within a capture area associated with the physical space;
selecting a mesh face included in the subset of mesh faces, where the mesh face is proximate to a surface of the real-world object; and
determining that the at least the portion of the object anchor includes the mesh face.
9. The computer-implemented method of claim 1 , wherein generating the association between the asset content and the object anchor comprises:
identifying a set of mesh faces, wherein each mesh face included in the set of mesh faces corresponds to a surface in the physical space;
selecting a subset of mesh faces from among the set of mesh faces, wherein at least a portion of each mesh face included in the subset of mesh faces is within a capture area associated with the physical space;
selecting a mesh face included in the subset of mesh faces, where the mesh face is proximate to a surface of the real-world object;
determining that an angle between the mesh face and the image is less than a threshold value; and
determining that the at least the portion of the object anchor includes the mesh face.
10. The computer-implemented method of claim 1 , wherein generating the association between the asset content and the object anchor comprises:
identifying a set of mesh faces, wherein each mesh face included in the set of mesh faces corresponds to a surface in the physical space;
selecting a subset of mesh faces from among the set of mesh faces, wherein at least a portion of each mesh face included in the subset of mesh faces is within a capture area associated with the physical space;
selecting a first mesh face included in the subset of mesh faces, wherein the first mesh face is proximate to a surface of the real-world object;
selecting a second mesh face included in the subset of mesh faces, wherein the second mesh face is proximate to the first mesh face; and
determining that the at least the portion of the object anchor includes the first mesh face and the second mesh face.
11. The computer-implemented method of claim 1 , wherein generating the association between the asset content and the object anchor comprises:
identifying a set of mesh faces, wherein each mesh face included in the set of mesh faces corresponds to a surface in the physical space;
selecting a subset of mesh faces from among the set of mesh faces, wherein at least a portion of each mesh face included in the subset of mesh faces is within a capture area associated with the physical space;
selecting a first mesh face included in the subset of mesh faces, wherein the first mesh face is proximate to a surface of the real-world object;
determining that a first angle between the first mesh face and the image is less than a first threshold value;
selecting a second mesh face included in the subset of mesh faces, wherein the second mesh face is proximate to the first mesh face;
determining that a second angle between the second mesh face and the first mesh face is less than a second threshold value; and
determining that the at least the portion of the object anchor includes the first mesh face and the second mesh face.
12. The computer-implemented method of claim 1 , further comprising:
encrypting a reference image associated with the object anchor to generate an encrypted reference image;
transmitting the encrypted reference image from a mobile device to an asset store server;
receiving a link to the encrypted reference image from the asset store server; and
transmitting the link from the mobile device to a data intake and query system.
13. The computer-implemented method of claim 1 , further comprising:
encrypting a reference image associated with the object anchor to generate an encrypted reference image;
transmitting the encrypted reference image from a mobile device to an asset store server;
receiving a link to the encrypted reference image from the asset store server; and
transmitting the link from the mobile device to a data intake and query system,
wherein the data intake and query system:
transmits the link to the asset store server;
receives the encrypted reference image from the asset store server;
decrypts the encrypted reference image to generate the reference image; and
stores the reference image in a key-value store.
14. The computer-implemented method of claim 1 , further comprising:
identifying a set of object anchors that is proximate to a beacon; and
determining that the object anchor is included in the set of object anchors.
15. The computer-implemented method of claim 1 , further comprising:
identifying a set of object anchors that is within a geofence; and
determining that the object anchor is included in the set of object anchors.