Abstract: System and method are provided for improving camera pose accuracy in augmented reality (AR) systems. The method detects and processes inconsistencies in captured camera poses by identifying locally rigid pose groups and matching visual features between images both within and across these groups. The process involves triangulating 3D landmarks within pose groups, establishing correspondences between groups, and performing bundle adjustment to optimize camera poses. This systematic approach enables the generation of accurate 3D models by detecting and correcting pose drift through feature matching, landmark triangulation, and global pose optimization across multiple camera positions and orientations.

Abstract: 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.

Abstract: Systems and methods are provided for scaling a 3-D representation of a building structure by selectively pairing camera poses generated by augmented reality frameworks. The geometric information provided by augmented reality frameworks enables scale for non-augmented reality cameras, such as SLAM derived camera solutions, associated with the augmented reality cameras. To reduce the noise and error that augmented reality frameworks can impart into their camera solves, only reliable augmented reality cameras are used for scale calculations of associated non augmented reality cameras. Reliable augmented reality cameras are identified based on translation distance analyses and comparisons. 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.

Abstract: The disclosure relates to methods, storage media, and systems of detecting a persisting or sustained blur condition across 2D image frames captured for a 3D reconstruction pipeline. It may include receiving a plurality of image frames captured by a camera of a capture device, receiving sensor data of the capture device, detecting, based on the sensor data of the capture device, a blur condition for at least a threshold number of image frames within a capture window, responsive to detecting the blur condition, providing an augmentation for at least one image frame of the plurality of image frames based on the sensor data, applying the augmentation to the at least one image frame of the plurality of image frames, and displaying, on a display of the capture device, the at least one augmented image frame.

Abstract: 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.

Abstract: Techniques are described for identifying correspondences between images to generate a fundamental matrix for the camera positions related to the images. The resultant fundamental matrix enables epipolar geometry to correlate common features among the images. Correspondences are identified by confirming feature matches across images by applying a homography to data representing features across images. Further techniques are described herein for generating a representation of a boundary of a feature of a structure based on a digital image. In one or more embodiments, generating a representation of a boundary of a particular feature in a digital image comprises determining a portion of the image that corresponds to the structure, and determining a portion of the image that corresponds to the particular feature. One more vanishing points are associated with the portion of the image corresponding to the particular feature.