Abstract: A method of training an object identification system and identifying three dimensional objects using semantic segments includes receiving, into a non-volatile memory, an input file containing a geometric description of a three dimensional object having one or more semantic segments and one or more annotations for each of the one or more semantic segments, receiving, into the non-volatile memory one or more training images of the three dimensional object, identifying, through a processor, the one or more segments in the one or more training images, computing, through a training module, one or more descriptors to the one or more segments, and generating an output file representing a machine vision of the three dimensional object.

Abstract: A method of training an object identification system and identifying three dimensional objects using semantic segments includes receiving, into a non-volatile memory, an input file containing a geometric description of a three dimensional object having one or more semantic segments and one or more annotations for each of the one or more semantic segments, receiving, into the non-volatile memory one or more training images of the three dimensional object, identifying, through a processor, the one or more segments in the one or more training images, computing, through a training module, one or more descriptors to the one or more segments, and generating an output file representing a machine vision of the three dimensional object.

Abstract: A method for photogrammetric texture mapping using casual images is provided. The method may include the following steps: estimating, for each vertex of at least a portion of a three dimensional (3D) mesh representing a model, projection parameters associated with a virtual camera that is unique for each vertex; mapping pixels from a two dimensional (2D) image to the vertices, such that each mapping of a pixel is based on the estimated respective virtual camera parameters; and texturing the portion of the mesh with corresponding mapped pixels wherein vertices on the textured portion are selected such that they are visible from a specified viewpoint associated with the 3D mesh.

Abstract: A method for photogrammetric texture mapping using casual images is provided. The method may include the following steps: estimating, for each vertex of at least a portion of a three dimensional (3D) mesh representing a model, projection parameters associated with a virtual camera that is unique for each vertex; mapping pixels from a two dimensional (2D) image to the vertices, such that each mapping of a pixel is based on the estimated respective virtual camera parameters; and texturing the portion of the mesh with corresponding mapped pixels wherein vertices on the textured portion are selected such that they are visible from a specified viewpoint associated with the 3D mesh.

Abstract: A system, method, and computer program product for automatically detecting and correcting the “purple fringing” effect, typically due to axial chromatic aberration in imaging devices, are disclosed and claimed. A chromaticity score is computed, denoting the amount of false color related to a purple fringing artifact. A locality score is computed, denoting the similarity of the purple fringing region to a shape of a narrow ridge, which is typical for purple fringing artifacts. A saturation score is also computed, denoting the proximity of a pixel to saturated pixels. These scores are then combined into a detection score, denoting pixels having strong indications they share properties common to pixels of purple fringing artifacts. The detected pixels are then correspondingly corrected, e.g. by chroma suppression. The scoring and correction may be performed over combinations of image resolutions, e.g. an original version and potentially numerous downscaled versions.

Abstract: A system, method, and computer program product for automatically detecting and correcting the “purple fringing” effect, typically due to axial chromatic aberration in imaging devices, are disclosed and claimed. A chromaticity score is computed, denoting the amount of false color related to a purple fringing artifact. A locality score is computed, denoting the similarity of the purple fringing region to a shape of a narrow ridge, which is typical for purple fringing artifacts. A saturation score is also computed, denoting the proximity of a pixel to saturated pixels. These scores are then combined into a detection score, denoting pixels having strong indications they share properties common to pixels of purple fringing artifacts. The detected pixels are then correspondingly corrected, e.g. by chroma suppression. The scoring and correction may be performed over combinations of image resolutions, e.g. an original version and potentially numerous downscaled versions.

Abstract: A method for photogrammetric texture mapping using casual images is provided. The method may include the following steps: estimating, for each vertex of at least a portion of a three dimensional (3D) mesh representing a model, projection parameters associated with a virtual camera that is unique for each vertex; mapping pixels from a two dimensional (2D) image to the vertices, such that each mapping of a pixel is based on the estimated respective virtual camera parameters; and texturing the portion of the mesh with corresponding mapped pixels wherein vertices on the textured portion are selected such that they are visible from a specified viewpoint associated with the 3D mesh.

Abstract: A system, method, and computer program product for automatically detecting and correcting the “purple fringing” effect, typically due to axial chromatic aberration in imaging devices, are disclosed and claimed. A chromaticity score is computed, denoting the amount of false color related to a purple fringing artifact. A locality score is computed, denoting the similarity of the purple fringing region to a shape of a narrow ridge, which is typical for purple fringing artifacts. A saturation score is also computed, denoting the proximity of a pixel to saturated pixels. These scores are then combined into a detection score, denoting pixels having strong indications they share properties common to pixels of purple fringing artifacts. The detected pixels are then correspondingly corrected, e.g. by chroma suppression. The scoring and correction may be performed over combinations of image resolutions, e.g. an original version and potentially numerous downscaled versions.

Abstract: A method for photogrammetric texture mapping using casual images is provided. The method may include the following steps: estimating, for each vertex of at least a portion of a three dimensional (3D) mesh representing a model, projection parameters associated with a virtual camera that is unique for each vertex; mapping pixels from a two dimensional (2D) image to the vertices, such that each mapping of a pixel is based on the estimated respective virtual camera parameters; and texturing the portion of the mesh with corresponding mapped pixels wherein vertices on the textured portion are selected such that they are visible from a specified viewpoint associated with the 3D mesh.