Abstract: A spin-estimation system may include an image-capturing sensor positioned and configured to capture images of an object within a field of view of the image-capturing sensor. The spin-estimation system may be configured to perform one or more operations to analyze spin properties of the object. The operations may include setting an image capture framerate that corresponds to a minimum spin motion of the object, printing an orientation marker on an outer surface of the object, and capturing, by the image-capturing sensor at the set image capture framerate, images of the object after starting motion of the object. The operations may include isolating the object in each image to generate isolated object images. The operations may include generating an object marker segmentation map based on the isolated object images. A spin rate and a spin axis may be estimated based on the object marker segmentation map using deep learning approaches.

Abstract: Disclosed are embodiments for determining the position and speed of a projectile in three-dimensional world coordinates using a single camera and radar. In some embodiments, a method comprises: determining a zero radial speed time of the projectile based on radar measurements of the projectile; determining a radial speed of the projectile at a particular time based on the radar measurements; determining a radial speed slope at the particular time based on the radial speed measurements; determining a two-dimensional image point of the projectile at the particular time; determining a depth scale coefficient at the particular time based on the zero radial speed time, the radial speed, the radial speed slope, the image point, and a homographic transformation; and determining a position of the projectile in space at the particular time based on a three-dimensional position of the camera, the depth scale coefficient, the image point and the homographic transformation.

Abstract: A spin-estimation system may include an image-capturing sensor positioned and configured to capture images of an object within a field of view of the image-capturing sensor. The spin-estimation system may be configured to perform one or more operations to analyze spin properties of the object. The operations may include setting an image capture framerate that corresponds to a minimum spin motion of the object, printing an orientation marker on an outer surface of the object, and capturing, by the image-capturing sensor at the set image capture framerate, images of the object after starting motion of the object. The operations may include isolating the object in each image to generate isolated object images. The operations may include generating an object marker segmentation map based on the isolated object images. A spin rate and a spin axis may be estimated based on the object marker segmentation map using deep learning approaches.

Abstract: Disclosed are embodiments for determining the position and speed of a projectile in three-dimensional world coordinates using a single camera and radar. In some embodiments, a method comprises: determining a zero radial speed time of the projectile based on radar measurements of the projectile; determining a radial speed of the projectile at a particular time based on the radar measurements; determining a radial speed slope at the particular time based on the radial speed measurements; determining a two-dimensional image point of the projectile at the particular time; determining a depth scale coefficient at the particular time based on the zero radial speed time, the radial speed, the radial speed slope, the image point, and a homographic transformation; and determining a position of the projectile in space at the particular time based on a three-dimensional position of the camera, the depth scale coefficient, the image point and the homographic transformation.

Abstract: Automatic club recognition during a golf swing is provided. At least one processor receives a series of images of a golf club captured during a golf swing. At least one processor detects from the series of images one or more sticker labels placed on the golf club. At least one processor classifies a golf club type of the golf club based on recognizing a marker, e.g., a unique or particular marker, coded on the one or more sticker labels, the marker for representing a specific type of golf club.

Abstract: A spin-estimation system may include an image-capturing sensor positioned and configured to capture images of an object within a field of view of the image-capturing sensor. The spin-estimation system may be configured to perform one or more operations to analyze spin properties of the object. The operations may include setting an image capture framerate that corresponds to a minimum spin motion of the object, printing an orientation marker on an outer surface of the object, and capturing, by the image-capturing sensor at the set image capture framerate, images of the object after starting motion of the object. The operations may include isolating the object in each image to generate isolated object images. The operations may include generating an object marker segmentation map based on the isolated object images. A spin rate and a spin axis may be estimated based on the object marker segmentation map using deep learning approaches.

Abstract: An interactive 3-D drawing method supports 3-D modeling of real-world scenes captured in the form of multiple images taken from different locations and angles. The method enables the user manipulate a 3-D drawing primitive without changing its appearance on a selected input image.

Abstract: An interactive 3-D drawing method supports 3-D modeling of real-world scenes captured in the form of multiple images taken from different locations and angles. The method enables the user manipulate a 3-D drawing primitive without changing its appearance on a selected input image.

Abstract: A method of determining a match between a candidate template and a super-template involves using the super-template to identify i) spatial coordinates for a plurality of minutiae that define an object, and ii) a quality associated with each minutiae. For sets of the super-template minutiae having at least two defined minutiae qualities, at least one Delaunay triangle is computed for each set. A match between the candidate template and the super-template is determined by determining a correspondence of Delaunay triangles in the candidate and super-templates, which correspondence results in an alignment of at least some minutiae of the candidate template with at least some minutiae of the super-template. Related methods, articles and apparatus are also disclosed.