An apparatus for generating location information of an object in a scene includes circuitry configured to: acquire image data of a scene from an image capture device; acquire predicted location information of an object in the scene indicative of a region of the scene in which the object is predicted to be located at a given time; detect one or more properties of the object from the image data, the properties of the object indicative of an observed location of the object in the scene; and generate location information of the object in the scene using the predicted location information and the one of more properties of the object.

In tracking of a moving body using image data in detecting a target moving body having few externally outstanding features, such as coloring and a shape, from an image in an image frame, if an image of the target moving body overlaps a background image largely and their colorings are the same or similar to one another, it is difficult to detect the target moving body. A template image of the target moving body is superimposed on a background image of a region (periphery) of a candidate position of the target to generate a composite image and the moving body is detected based on a degree of match calculated through comparison of the composite image with an image of the region (periphery) of the candidate position of the target.

Systems and methods are described for generating a three-dimensional track of a ball in a gaming environment from multiple cameras. In some examples, at least two input videos, each including frames of a ball moving in a gaming environment recorded by a camera, may be obtained, along with a camera projection matrix that maps a two-dimensional pixel space representation to a three-dimensional representation of the gaming environment. Candidate two-dimensional image locations of the ball across the plurality of frames of the at least two input videos may be identified using neural network or computer vision techniques. An optimization algorithm may be performed that uses a 3D ball physics model, the camera projection matrix and a subset of the candidate two-dimensional image locations of the ball from the at least two input videos to generate a three-dimensional track of the ball in the gaming environment.

A method includes identifying a first point on an object striking element in a first image and a second image from images. The first and second images are captured within a predetermined time span of an impact of the object with the element and determining an impact time of the impact in combination with determining a position in the first and/or second images corresponding to a location of the object at the impact time. Based on the positions of the first point in the first and second images, determining a position in the first and/or second images corresponding to a position of the first point at the impact time. The method also includes determining a distance from the imager to a location at which the object and the element impact one another and determining an impact location of the object relative to the first point.

A scoring system is disclosed for a shuffleboard table 2 having a sliding surface 4 on which a puck 6 can be thrown. A camera 26 is arranged to point in a direction 28 that is angled relative to the normal 30 of the sliding surface 4. A puck 6 can be thrown and a computer 32 can detect a moving object within a throwing zone 16. The computer 32 analyses whether the detected moving object corresponds to a valid puck. When all pucks are stationary on the sliding surface 4 the computer 32 can calculate a score.

An apparatus for predicting whether an object moving across a surface will reach a target destination is provided, the apparatus comprising circuitry configured to: receive a first image and one or more subsequent second images from a camera; identify a location of an object on a surface in the first image; identify a location of the object on the surface in one or more of the second images; determine one or more motion characteristics of the object based on the location of the object in the first image and the location of the object in the one or more second images; generate a predicted path of the object across the surface based on a model of the surface and the motion characteristics of the object; and generate a prediction of whether the object will reach the target destination based on the predicted path of the object and the location of the target destination.

The prediction control part 204 predicts a three-dimensional position and a three-dimensional velocity of the world coordinate system of the flying ball at a specific time after the initial time as a predicted position and a predicted velocity based on initial position and initial velocity of flying ball, and an equation indicating a parabolic shape of the flying ball. The conversion control part 205 converts the predicted position into a two-dimensional position of a camera coordinate system as a temporary position. The acquisition control part 206 specifies a flying ball image and acquires a two-dimensional position of the camera coordinate system of the flying ball image as an observation position. The correction control part 207 corrects the predicted position and the predicted velocity as a corrected position and a corrected velocity based on the predicted position and the predicted velocity, the observation position, and a Kalman filter.

A method of generating a path of an object through a virtual environment is provided, the method comprising: receiving image data, at a first instance of time, from a plurality of image capture devices arranged in a physical environment; receiving image data, at an at least one second instance of time after the first instance of time, from a plurality of image capture devices arranged in the physical environment; detecting a location of a plurality of points associated with an object within the image data from each image capture device at the first instance of time and the at least one second instance of time; projecting the location of the plurality of points associated with the object within the image data from each image capture device at the first instance of time and the at least one second instance of time into a virtual environment to generate a location of the plurality of points associated with the object in the virtual environment at each instance of time; and generating a path of the object through the virtual environment using the location of the plurality of points associated with the object in the virtual environment, the path being indicative of the position and orientation of the object through the virtual environment.

A golfing aid system and method includes an image capturing device and an interface system coupled to at least one processor and a memory coupled to the processor which is configured to be capable of executing programmed instructions comprising and stored in the memory to capture, with the image capture device, image data comprising at least one of a playing surface, a ball, or a designated location spaced from the ball on the playing surface. At least one type of spatial data and at least one type of playing surface data relating to the playing surface, the ball and the designated location is determined. An overall trajectory, a starting direction, and an initial velocity of the ball to reach the designated location is computed, wherein the computation identifies and accounts for at least one airborne segment. The computed overall trajectory, the starting direction, and the initial velocity of the ball are provided.

Systems and methods are described for generating a three-dimensional track a ball in a gaming environment from a single camera. In some examples, an input video including frames of a ball moving in a gaming environment recorded by a camera may be obtained, along with a camera projection matrix associated with at least one frame that maps a two-dimensional pixel space representation to a three-dimensional representation of the gaming environment. Candidate two-dimensional image locations of the ball across the plurality of frames may be identified using a neural network or a computer vision algorithm. An optimization algorithm may be performed that uses a 3D ball physics model, the camera projection matrix and a subset of the candidate two-dimensional image locations of the ball to generate a three-dimensional track of the ball in the gaming environment. The three-dimensional track of the ball may then be provided to a user device.