Intel Corporation

Yumeng Wang

Wenlong Li

Qiang Li

Xiaofeng Tong

Chen Ling

Yikai Fang

Ming Lu

Hongzhi Tao

Doron T Houminer

Haihua Lin

Hang Zheng

Chenning Liu

A system () includes multiple cameras () disposed about an area (), a processor (), and a memory () communicatively coupled to the processor. The memory stores instructions that cause the processor to receive a set of video data () associated with the cameras. In an embodiment, the set of video data includes a set of image frames associated with a set of ball tracking data (). In an embodiment, the operations include selecting a first image frame () associated with a first change in acceleration and a second image frame () associated with a second change in acceleration. In an embodiment, the operations include generating a set of virtual camera actions () based on the first image frame and the second image frame.

Systems and methods for virtual camera highlight creation

Methods, systems and apparatuses may provide for technology that detects an individual in a real-time multi-camera video feed and generates three-dimensional (3D) skeletal data based on the real-time multi-camera video feed. The technology may also automatically identify a frontal body orientation of an individual based on the 3D skeletal data and one or more anthropometric constraints.

Technology to automatically identify the frontal body orientation of individuals in real-time multi-camera video feeds

A method for trajectory generation based on player tracking is described herein. The method includes determining a temporal association for a first player in a captured field of view and determining a spatial association for the first player. The method also includes deriving a global player identification based on the temporal association and the spatial association and generating a trajectory based on the global player identification.

Player trajectory generation via multiple camera player tracking

Methods, systems and apparatuses may provide for technology that selects a player from a plurality of players based on an automated analysis of two-dimensional (2D) video data associated with a plurality of cameras, wherein the selected player is nearest to a projectile depicted in the 2D video data. The technology may also track a location of the selected player over a subsequent plurality of frames in the 2D video data and estimate a location of the projectile based on the location of the selected player over the subsequent plurality of frames.

Technology to automatically locate ball-holding players in multi-camera video feeds

A multi-camera architecture for detecting and tracking a ball in real-time. The multi-camera architecture includes network interface circuitry to receive a plurality of real-time videos taken from a plurality of high-resolution cameras. Each of the high-resolution cameras simultaneously captures a sports event, wherein each of the plurality of high-resolution cameras includes a viewpoint that covers an entire playing field where the sports event is played. The multi-camera architecture further includes one or more processors coupled to the network interface circuitry and one or more memory devices coupled to the one or more processors. The one or more memory devices includes instructions to determine the location of the ball for each frame of the plurality of real-time videos, which when executed by the one or more processors, cause the multi-camera architecture to simultaneously perform one of a detection scheme or a tracking scheme on a frame from each of the plurality of real-time videos to detect the ball used in the sports event and perform a multi-camera build to determine a location of the ball in 3D for the frame from each of the plurality of real-time videos using one of detection or tracking results for each of the cameras.

Multi-cam ball location method and apparatus

Method, systems and apparatuses may provide for technology that extracts one or more motion features from filtered position data associated with a projectile in a game and identifies a turning point in a trajectory of the projectile based on the one or more motion features. The technology may also automatically designate the turning point as a highlight moment if one or more of the turning point or the trajectory satisfies a proximity condition with respect to a target area in the game.

Highlight moment identification technology in volumetric content creation systems

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.

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Beijing, China

Yumeng Wang