A system and method for calibrating and re-calibrating an imaging device. The image device includes at least one varying intrinsic or extrinsic parameter value based on a view of 3D shapes and a 2D template therefor. The method and system are operable to receive a sequence of images from the imaging device, wherein a planar surface with known geometry is observable from the sequence of images; perform an initial estimation of a set of camera parameters for a given image frame; perform a parameter adjustment operation to minimize a dissimilarity between the template and the sequence of images; perform a parameter adjustment operation to maximize similarities in either the camera's coordinate system or the template's coordinate system; and update an adaptive world template to incorporate an additional stable point from the observed images to the template.

A generation device of a three-dimensional model including: an acquisition unit configured to acquire a first mask image indicating a structure area, which is an object still within each image captured from a plurality of viewpoints, and a second mask image indicating a foreground area, which is a moving object within each image captured from the plurality of viewpoints; a combination unit configured to generate a third mask image that integrates the structure area and the foreground area within the image captured from the plurality of viewpoints by combining the first mask image and the second mask image both acquired; and a generation unit configured to generate a three-dimensional model including the structure and the foreground by a visual volume intersection method using the third mask image.

Methods, systems, graphical user interfaces (GUIs), and computer-readable media for presenting GUI elements generated based on information associated with an event are generally described. An event information presentation system may be configured to present GUI elements generated based on substantially real-time event information associated with a live event, such as a sporting event. Illustrative event information may include object movement and location information for objects such as event participants (for instance, players) and articles (for instance, a football for a football game event). The event information may be interpreted based on activity categories to automatically differentiate, organize, highlight, or the like the event information in order to generate relevant and meaningful GUI elements.

Methods, systems, and computer-program products used for assessing athletic ability and generating performance data. In one embodiment, athlete performance data is generated through computer-vision analysis of video of an athletic performing, e.g., during practice or gameplay. The generated performance data for the athlete may include, for example, maximum speed, maximum acceleration, time to maximum speed, transition time (e.g., time to change direction), closing speed (e.g., time to close the distance to another athlete), average separation (e.g., between the athlete and another athlete), play-making ability, athleticism (e.g., a weighted computation and/or combination of multiple metrics), and/or other performance data. This performance data may be used to generate and/or update a profile associated with the athlete, which can be utilized for recruiting, scouting, comparing, and/or assessing athletes with greater efficiency and precision.

Apparatus and method for determining a quality score for virtual video cameras. For example, one embodiment comprises: a region of interest (ROI) detector to detect regions of interest within a first image generated from a first physical camera (PCAM) positioned at first coordinates; virtual camera circuitry and/or logic to generate a second image positioned at the first coordinates; image comparison circuitry and/or logic to establish pixel-to-pixel correspondence between the first image and the second image; an image quality evaluator to determine a quality value for the second image by evaluating the second image in view of the first image.

A system for monitoring objects at sporting events or other types of events uses a wearable drone that has at least one camera or other sensor for capturing or otherwise sensing data. When the drone is to be used for monitoring, such as monitoring an object at a sporting event, the wearable drone may be detached from its user, and it may hover or otherwise fly within a certain position of an object to be monitored. While flying, the drone's sensor may be used to capture information, such as performance data or images, of the object during the sporting event.

A system and method for determining an absolute position of an object in an area is presented. The system includes a server having a processor, and a plurality of camera nodes coupled to the server. Each node includes a camera that acquires images of the object and area. The server receives image data from a camera, detects the object within an approximate location by image analysis techniques, and determines a relative position of the object in pixel coordinates. The processor then detects stationary markers proximate to the relative location of the object, determines an absolute position of the detected markers relative to known markers to define an absolute position of the marker, and determines an absolute location of the object in relation to the absolute location of the detected marker. This absolute position of the object is provided to an official to accurately locate the object in the area.

A generation device of a three-dimensional model including: an acquisition unit configured to acquire a first mask image indicating a structure area, which is an object still within each image captured from a plurality of viewpoints, and a second mask image indicating a foreground area, which is a moving object within each image captured from the plurality of viewpoints; a combination unit configured to generate a third mask image that integrates the structure area and the foreground area within the image captured from the plurality of viewpoints by combining the first mask image and the second mask image both acquired; and a generation unit configured to generate a three-dimensional model including the structure and the foreground by a visual volume intersection method using the third mask image.

Methods and systems are described for registering a sports field to a video. Video of a live event may feature participants at a venue. A template of the venue, including virtual markings that represent real markings on the venue, may be obtained. A homographic transformation between an image plane and a ground plane may be determined by matching virtual markings to corresponding real markings captured in at least one frame of the video. The determined homographic transformation may be used in the automated analysis of sports statistics and in improving inserted annotations and visualizations.

The tennis self-training system according to an embodiment of the present invention comprising a control device comprising recording unit configured to record a tennis game and a processor configured to analysis the tennis game based on a video obtained from the recording unit; and a ball machine unit configured to move and launch a ball according to the instructions of the control device; wherein the control device is configured to: determine the position of a player and the position of the ball machine unit based on the video, predict a falling position of the ball hit by the player based on the video, calculate a ball launch position and a ball arrival position of the ball machine unit based on the position of the player and the falling position of the ball, generate a control signal related to the ball launch position and the ball arrival position, transmit the control signal to the ball machine unit, wherein the ball machine unit is configured to: receive the control signal from the control device, move to the ball launch position indicated by the received control signal, and launch the ball to the ball arrival position indicated by the received control signal.