Abstract: Methods of and systems for analyzing a multidimensional surface are disclosed. A parametric 3D surface of an object of interest is calculated for a surface of the object of interest defined in a 3D point cloud. A sufficiency of the parametric 3D surface is determined by evaluating a distance between the parametric 3D surface and the surface of the object of interest defined in the 3D point cloud. If the parametrical 3D surface is determined not to be sufficient, the parameters of the parametric 3D surface are modified, and the parametric 3D surface is calculated again. If the parametric 3D surface is determined to be sufficient, the parametric 3D surface is positioned on the surface of the object of interest defined in the 3D point cloud and some 3D data points of the object of interest are removed if they are above a certain distance from the parametric 3D surface.

Abstract: The disclosed systems, structures, and methods are directed to generating data points in a 3D point cloud generated from a plurality of images of an object, each image having been captured by an imaging mobile device from a corresponding point of view. The method comprises identifying, for identified feature points of the object, a list of 3D coordinates, and a list of 2D coordinates, an entry of said list being 2D coordinates of a projection of the feature data point on the corresponding image. In response to determining that, for a given feature point, a number of images on which the corresponding projected 2D coordinates fall onto a pixel range of said images is above a pre-determined threshold, the given feature point is marked as a robust feature point. A median feature point is generated from the list of 3D coordinates of the robust feature point.

Abstract: Systems and methods for generating a dataset associated with an object-of-interest. The method includes acquiring, by an imaging system, a stream of images of the object-of-interest and analyzing the stream of images by determining whether one or more capture constraint is met. The analysis is performed by continuously executing the following steps. If one or more capture characteristics is met for a portion of the stream of images, the portion of the stream of images is buffered thereby defining the dataset, the dataset being fitted for further processing. If the one or more capture characteristic is not met for the portion of the stream of images, the buffering is precluded until determination is made that the capture characteristic of a subsequent portion of the stream of images is met. The analyzing of the stream of images is stopped in response to a stopping condition is met.

Abstract: Methods of and systems for determining a characteristic distance of an object-of-interest. The method includes accessing a two-dimensional (2D) image of the object-of-interest, the 2D image comprising a plurality of pixels, each pixel being associated with a depth value indicative of a distance between an image sensing device that captured the 2D image and an entity present in the 2D image on the pixel, determining a contour of the object-of-interest on the 2D image, the contour defining an outline of the object-of-interest on the 2D image, determining an anchor pixel of the object-of-interest based on the contour thereof, determining a target segment on the 2D image and determining a length of the target segment based on a pixel length thereof and the depth value of a given pixel of the 2D image, the length of the target segment being the characteristic distance of the object-of-interest.

Abstract: The disclosed systems, structures, and methods are directed to generating data points in a 3D point cloud generated from a plurality of images of an object, each image having been captured by an imaging mobile device from a corresponding point of view. The method comprises identifying, for identified feature points of the object, a list of 3D coordinates, and a list of 2D coordinates, an entry of said list being 2D coordinates of a projection of the feature data point on the corresponding image. In response to determining that, for a given feature point, a number of images on which the corresponding projected 2D coordinates fall onto a pixel range of said images is above a pre-determined threshold, the given feature point is marked as a robust feature point. A median feature point is generated from the list of 3D coordinates of the robust feature point.