3-D Reconstruction Using Augmented Reality Frameworks
System and method are provided for scaling a 3-D representation of a building structure. The method includes obtaining world map data including a first track of real-world poses for a plurality of images. The plurality of images comprises non-camera anchors. The method also includes detecting a discrepancy in at least one real-world pose of the first track. The method also includes in response to detecting a discrepancy, generating a new track of real-world poses. The method also includes calculating a scaling factor for a 3-D representation of the building structure based on sampling across a plurality of tracks. The plurality of tracks comprises at least the first track and the new track.
1 - 20 . (canceled)
21 . A method for scaling a virtual representation of a building structure, the method comprising:
obtaining a plurality of images of the building structure, wherein the plurality of images comprises non-camera anchors;
identifying reference sensor data for respective ones of the plurality of images based on the non-camera anchors;
selecting at least two candidate poses based on one or more of the reference sensor data and the non-camera anchors; and
generating the virtual representation of the building structure based on correlating the reference sensor data with the at least two candidate poses.
22 . The method of claim 21 , wherein the non-camera anchors are image features.
23 . The method of claim 21 , wherein the virtual representation is a three-dimensional (3D) representation.
24 . The method of claim 21 , wherein the virtual representation is scaled using positional data in the reference sensor data of the at least two candidate poses.
25 . The method of claim 21 , wherein the reference sensor data is received via an augmented reality (AR) software framework.
26 . The method of claim 25 , wherein the at least two candidate poses are selected based on difference data between AR reference data and the non-camera anchors in at least two of the plurality of images.
27 . The method of claim 26 , wherein the difference data comprises a derived path shape divergence for at least the AR reference data.
28 . The method of claim 26 , wherein the virtual representation is scaled using positional data in the reference sensor data of the at least two candidate poses.
29 . A system for scaling a virtual representation of a building structure, comprising:
one or more processors;
a memory storing one or more programs configured for execution by the one or more processors, the one or more programs comprising instructions configurable for:
obtaining a plurality of images of the building structure, wherein the plurality of images comprises non-camera anchors;
identifying reference sensor data for respective ones of the plurality of images based on the non-camera anchors;
selecting at least two candidate poses based on one or more of the reference sensor data and the non-camera anchors; and
generating the virtual representation of the building structure based on correlating the reference sensor data with the at least two candidate poses.
30 . The system of claim 29 , wherein the non-camera anchors are image features.
31 . The system of claim 29 , wherein the virtual representation is a three-dimensional (3D) representation.
32 . The system of claim 29 , wherein the virtual representation is scaled using positional data in the reference sensor data of the at least two candidate poses.
33 . The system of claim 29 , wherein the reference sensor data is received via an augmented reality (AR) software framework.
34 . The system of claim 33 , wherein the at least two candidate poses are selected based on difference data between AR reference data and the non-camera anchors in at least two of the plurality of images.
35 . The system of claim 34 , wherein the difference data comprises a derived path shape divergence for at least the AR reference data.
36 . The system of claim 34 , wherein the virtual representation is scaled using positional data in the reference sensor data of the at least two candidate poses.
37 . One or more non-transitory computer readable storage medium storing one or more programs configured for execution by one or more processors, the one or more programs comprising instructions for:
obtaining a plurality of images of the building structure, wherein the plurality of images comprises non-camera anchors:
identifying reference sensor data for respective ones of the plurality of images based on the non-camera anchors;
selecting at least two candidate poses based on one or more of the reference sensor data and the non-camera anchors; and
generating the virtual representation of the building structure based on correlating the reference sensor data with the at least two candidate poses.
38 . The one or more non-transitory computer readable storage medium of claim 37 , wherein the non-camera anchors are image features.
39 . The one or more non-transitory computer readable storage medium of claim 37 , wherein the virtual representation is a three-dimensional (3D) representation.
40 . The one or more non-transitory computer readable storage medium of claim 37 , wherein the virtual representation is scaled using positional data in the reference sensor data of the at least two candidate poses.
41 . The one or more non-transitory computer readable storage medium of claim 37 , wherein the reference sensor data is received via an augmented reality (AR) software framework.
42 . The one or more non-transitory computer readable storage medium of claim 41 , wherein the at least two candidate poses are selected based on difference data between AR reference data and the non-camera anchors in at least two of the plurality of images.
43 . The one or more non-transitory computer readable storage medium of claim 42 , wherein the difference data comprises a derived path shape divergence for at least the AR reference data.
44 . The one or more non-transitory computer readable storage medium of claim 42 , wherein the virtual representation is scaled using positional data in the reference sensor data of the at least two candidate poses.