Systems, methods, and media for modifying the coloring of images utilizing machine learning

    公开(公告)号:US12020364B1

    公开(公告)日:2024-06-25

    申请号:US17715500

    申请日:2022-04-07

    IPC分类号: G06T15/04 G06T3/40 G06T7/90

    摘要: Techniques are provided for modifying coloring of images utilizing machine learning. A trained model is generated utilizing machine learning with training data that includes images of a plurality of different scenes with different illumination characteristics. New original images of a scene may each be downsampled and transformed to a corresponding output image utilizing the trained model. A color transformation from each original image to its corresponding output image may be determined. In an embodiment, the color transformation is determined utilizing a spline fitting approach. The determined color transformations may be applied to each of the original images to generate corrected images. Specifically, the color transformation that is applied to a particular original image is the color transformation determined for the input image that corresponds to the particular original image. The corrected images are utilized to generate a digital model of the scene, and the digital model has accurate model texture.

    Determining camera rotations based on known translations

    公开(公告)号:US11790606B2

    公开(公告)日:2023-10-17

    申请号:US17368477

    申请日:2021-07-06

    发明人: Luc Robert

    IPC分类号: G06T17/20 G06T7/70 G06T7/579

    摘要: In example embodiments, techniques are provided for calculating camera rotation using translations between sensor-derived camera positions (e.g., from GPS) and pairwise information, producing a sensor-derived camera pose that may be integrated in an early stage of SfM reconstruction. A software process of a photogrammetry application may obtain metadata including sensor-derived camera positions for a plurality of cameras for a set of images and determine optical centers based thereupon. The software process may estimate unit vectors along epipoles from a given camera of the plurality of cameras to two or more other cameras. The software process then may determine a camera rotation that best maps unit vectors defined based on differences in the optical centers to the unit vectors along the epipoles. The determined camera rotation and the sensor-derived camera position form a sensor-derived camera pose that may be returned and used.

    DETERMINING CAMERA ROTATIONS BASED ON KNOWN TRANSLATIONS

    公开(公告)号:US20230007962A1

    公开(公告)日:2023-01-12

    申请号:US17368477

    申请日:2021-07-06

    发明人: Luc Robert

    IPC分类号: G06T17/20 G06T7/579 G06T7/70

    摘要: In example embodiments, techniques are provided for calculating camera rotation using translations between sensor-derived camera positions (e.g., from GPS) and pairwise information, producing a sensor-derived camera pose that may be integrated in an early stage of SfM reconstruction. A software process of a photogrammetry application may obtain metadata including sensor-derived camera positions for a plurality of cameras for a set of images and determine optical centers based thereupon. The software process may estimate unit vectors along epipoles from a given camera of the plurality of cameras to two or more other cameras. The software process then may determine a camera rotation that best maps unit vectors defined based on differences in the optical centers to the unit vectors along the epipoles. The determined camera rotation and the sensor-derived camera position form a sensor-derived camera pose that may be returned and used.