A kinetic motion learning device includes an information storage unit configured to associate and store in advance a pitching motion video and pitching trajectory information for a plurality of pitches actually delivered by a pitcher on a potential opponent team, and is configured to read a set of the pitching motion video and the pitching trajectory information stored in the information storage unit, output the pitching motion video being read to a projector, output the pitching trajectory information being read to a pitching machine, and control motion timings of the projector and the pitching machine so that a time of ball release of the pitcher in the pitching motion video displayed on a screen and a time of the pitching machine launching the ball with the pitching trajectory information match. The projector is configured to project the pitching motion video onto the screen so that the pitching motion video is displayed on the screen at a motion timing controlled by the kinetic motion learning device. The screen includes a hole through which a ball launched by the pitching machine can pass at a position of ball release of the pitcher in the pitching motion video displayed.

An information processing system for obtaining an audio content file for video data providing video content representing a sport event, including: a receiver configured to receive a data stream including the video data; a preference data obtainer configured to obtain preference data, wherein the preference data indicate a selected competitor participating in the sport event; a category identifier obtainer configured to obtain a category identifier from a machine learning algorithm into which the video data is input, wherein the machine learning algorithm is trained to classify a scene represented in the video content into a category of a predetermined set of categories associated with the sport event, wherein the category identifier indicates the category into which the scene is classified; an audio content file obtainer configured to obtain, based on the obtained category identifier and the obtained preference data, the audio content file from a prestored set of audio content files, wherein the audio content file provides audio content associated with the category of the scene and the preference data; and a synchronizer configured to synchronize the audio content and the video content for synchronized play back of the scene by a media player configured to play back the video content and the audio content file.

Systems and methods for improved operations of ski lifts increase skier safety at on-boarding and off-boarding locations by providing an always-on, always-alert system that “watches” these locations, identifies developing problem situations, and initiates mitigation actions. One or more video cameras feed live video to a video processing module. The video processing module feeds resulting sequences of images to an artificial intelligence (AI) engine. The AI engine makes an inference regarding existence of a potential problem situation based on the sequence of images. This inference is fed to an inference processing module, which determines if the inference processing module should send an alert or interact with the lift motor controller to slow or stop the lift.

A highlight learning technique is provided to detect and identify highlights in sports videos. A set of event models are calculated from low-level frame information of the sports videos to identify recurring events within the videos. The event models are used to characterize videos by detecting events within the videos and using the detected events to generate an event vector. The event vector is used to train a classifier to identify the videos as highlight or non-highlight.

The present invention relates to a method for deriving a 3D data from image data comprising: receiving, from at least one camera, image data representing an environment; detecting, from the image data, at least one object within the environment; classifying the at least one detected object, wherein the method comprises, for each classified object of the classified at least one objects: determining a 2D skeleton of the classified object by implementing a neural network to identify features of the classified object in the image data corresponding to the classified object; and constructing a 3D skeleton for the classified object, comprising mapping the determined 2D skeleton to 3D.

Systems and methods for improved operations of ski lifts increase skier safety at on-boarding and off-boarding locations by providing an always-on, always-alert system that “watches” these locations, identifies developing problem situations, and initiates mitigation actions. One or more video cameras feed live video to a video processing module. The video processing module feeds resulting sequences of images to an artificial intelligence (AI) engine. The AI engine makes an inference regarding existence of a potential problem situation based on the sequence of images. This inference is fed to an inference processing module, which determines if the inference processing module should send an alert or interact with the lift motor controller to slow or stop the lift.

Disclosed herein is a system and method directed to object tracking and metric generation using a plurality of cameras. The system includes the plurality of cameras disposed around a playing surface in a mirrored configuration, where the plurality of cameras are time-synchronized. The system further includes logic that, when executed by a processor, causes performance of operations including: obtaining a sequence of images from the plurality of cameras, continuously detecting an object in image pairs at successive points in time, wherein each image pair corresponds to a single point in time, continuously determining a location of the object within the playing space through triangulation of the object within each image pair, detecting a player and the object within each image of a subset of image pairs of the sequence of images, identifying a sequence of interactions between the object and the player, and storing the sequence of interactions.

Techniques and systems are provided for generating media content. For example, a server computer can detect a trigger from a device located at a site. The trigger is associated with an event at the site. The server computer can obtain media segments of media captured by a plurality of media capture devices located at the site. At least one of the media segments corresponds to the detected trigger. The server computer can determine one or more quality metrics of a media segment based on a first motion of an object captured in the media segment and/or a second motion of a media capture device used to capture the media segment. A subset of media segments can be selected from the obtained media segments based on quality metrics determined for the obtained media segments. A collection of media segments including the subset of media segments can then be generated.

Embodiments relate to systems, methods and computer readable media for gaming monitoring. In particular, embodiments process images to determine presence of a gaming object on a gaming table in the images. Embodiments estimate postures of one or more players in the images and based on the estimated postures determine a target player associated with the gaming object among the one or more players.

Techniques related to performing object or person association or correspondence in multi-view video are discussed. Such techniques include determining correspondences at a particular time instance based on separately optimizing correspondence sub-matrices for distance sub-matrices based on two-way minimum distance pairs between frame pairs, generating and fusing tracklets across time instances, and adjusting correspondence, after such tracklet processing, via elimination of outlier object positions and rearrangement of object correspondence.