A clip image to be used as a highlight image, a replay image, or the like in a broadcast or the like is enabled to be generated easily and precisely. For this purpose, an information processing apparatus performs first processing for converting a received image signal into an image signal for real-time processing and transmitting the image signal to an analysis engine that is located outside. Furthermore, the information processing apparatus performs second processing for receiving event extraction information that has been received from the analysis engine and generating setting information of a clip image, by using the event extraction information.

This ball game video analysis device: receives movie frames captured by cameras; computes the trajectory of the three-dimensional positions of a ball using the received multiple movie frames; determines, on the basis of a change in the ball trajectory, whether or not any action has been made by a player with respect to the ball; in the case when there has been such an action, selects, as an action frame, the movie frame corresponding to the timing at which said action was made; and identifies, from the action frame, a player who made that action.

Techniques for padding audiovisual clips (for example, audiovisual clips of sporting events) for the purpose of causing the clip to have a predetermined duration so that the padded clip can be evaluated for viewer interest by a machine learning (ML) algorithm. The unpadded clip is padded with audiovisual segment(s) that will cause the padded clip to have a level of viewer interest that it would have if the unpadded clip had been longer. In some embodiments the padded segments are synthetic images generated by a generative adversarial network such that the synthetic images would have the same level of viewer interest (as adjudged by an ML algorithm) as if the unpadded clip had been shot to be longer.

Embodiments of the present invention provide a method, system and computer program product for exciting moment notification for a live event. An exciting moment notification method includes first defining in a table in memory of a computer, an exciting moment occurring during a live event, such as a card game, awards program or a sporting event, and then annotating a multiplicity of images of different instances of the live event with the exciting moment. The method further includes video streaming a live instance of the live event over a computer communications network and matching a frame of the video streamed live instance in the memory of the computer to an annotated one of the multiplicity of images. Finally, the method includes transmitting a message to at least one subscriber of the instance of the live event indicating an occurrence of the exciting moment.

An image generation apparatus obtains a virtual viewpoint image generated based on captured images obtained by image capture of an object by a plurality of image capture devices from a plurality of viewpoints and three-dimensional shape data on the object, and removes noise in the virtual viewpoint image obtained, the noise being generated due to accuracy of the three-dimensional shape data.

A system and method are described, for automatically analyzing and understanding individual and group activities and interactions. The method includes receiving at least one image from a video of a scene showing one or more individual objects or humans at a given time; applying at least one machine learning or artificial intelligence technique to automatically learn a spatial, temporal or a spatio-temporal informative representation of the image and video content for activity recognition; and identifying and analyzing individual and group activities in the scene.

A data processing method comprising obtaining information identifying a position of an object in a scene at a time during a sporting event; obtaining an image of the scene captured at the time during the sporting event; projecting the position of the object in the scene onto an image plane of the image; and outputting information based on the projection.

A video capture and processing system includes a memory configured to store a pose database. The pose database includes poses that indicate a start or stoppage in an event. The system also includes a processor operatively coupled to the memory. The processor is configured to generate a pose of an individual in a video frame of captured video of the event. The pose can be three-dimensional pose or a two-dimensional pose. The processor is also configured to determine, based on the pose database, whether the pose of the individual indicates a start or a stoppage in the event. The processor is further configured to control an upload of video of the event based on the determination of whether the pose indicates the start or the stoppage in the event.

A learning data generation device for generating learning data for learning a recognizer capable of estimating a contour of a sphere making spinning motion, with high accuracy, the sphere being recorded in a single camera video image, is provided. The learning data generation device includes: a spinning rate estimation unit that receives an input of a learning video image in which motion of a spinning sphere is recorded and an initial value of a size of a contour of the recorded sphere in the video image, sets a plurality of set values of the size of the contour based on the initial value, and obtains an estimated value of a spinning rate of the sphere based on the learning video image, for each of the set values; a contour determination unit that receives an input of a true value of the spinning rate of the sphere, the true value being obtained in advance for the learning video image, and determines at least any of a plurality of the set values respectively corresponding to a plurality of the estimated values selected in order of closeness to the true value, as a determined value of the contour; and a learning data output unit that outputs the learning video image and the determined value as learning data.

Methods and systems for determining a ball shot attempt location on a ball court are disclosed. The method includes receiving an input video, where the input video includes the ball shot attempt and one or more players; receiving a declared ball shot attempt; determining a potential shooter by detecting a moving object flow in the input video; determining a potential shooter image region in the image plane by analyzing an overlapping image area of the ball trajectory and the potential shooter; determining a shooter foot-on-court time; determining a most probable pair of shooter legs in the potential shooter image region; determining a shooter foot location based on the most probable pair of shooter legs; and determining a ball shot attempt location on the ball court by applying a camera projection to the shooter foot location.