For one embodiment of the present invention, a method of object instance edge detection and segmentation is described. The method includes obtaining an input image with a shape and extracting, with a feature extractor of a point supervised transformer model, a hierarchical combination of features from the input image including a set of feature maps having different levels. The method further includes receiving, with a transformer decoder, an output including a feature map from the feature extractor, and object queries each with d dimensions, training the point supervised transformer model with a sparse set of keypoint annotations along a boundary of each object instance, and generating a box prediction, a classification prediction, and a coefficient prediction for each object instance based on an output from the transformer decoder.

A digital content production center and method are described. An illustrative method includes receiving object information from a plurality of different sensors, where a first sensor in the plurality of sensors provides first sensor data to describe the object information and where a second sensor in the plurality of sensors provides second sensor data to describe the object information. The method further includes determining that the first sensor data and not the second sensor data, thereby differentiating sensor data information, is to be used in connection with building an image of an object described by the object information, generating a set of prioritized data streams that include digital representations of the first sensor data and not necessarily the second sensor data, and transmitting the data streams across a communication network, according to a prioritization.

A multi-mode tracking method according to the present disclosure includes receiving sensor signals from a plurality of positioning sensors located on a plurality of sport participants wherein the sensor signals each include a participant identifier and location data, receiving a sport image captured from a camera located near a playfield wherein the sport image includes at least a target participant among a plurality of sport participants on the playfield, detecting an occlusion related to the target participant in the sports image, determining the severity of the occlusion on the basis of a sensor signal received from a specific positioning sensor installed on a specific sport player located in a region of interest related to the occlusion, and determining a location of the sport participant on the basis of the severity of the occlusion.

The present disclosure is related to an inspection system capable of inspecting a plurality of gaming chips. A game chip of the plurality of game chips includes a wireless tag storing first chip information and to which the optically readable second chip information is on a side of the game chip. The inspection system includes an inspection device configured to inspect one or more game chips. The inspection device includes a wireless tag reader configured to read the wireless tag of the game chip and acquire the first chip information. The inspection device includes a camera configured to reading the side surface of the game chip to obtain the second chip information. The inspection device includes a unit configured to determine whether the game chip passes one or more rules based on the first chip information and the second chip information.

An apparatus which accurately analyzes a motion state of an exercise appliance and performs a notification of the accurately analyzed motion state. A sensor unit includes a sensor section that is attached to a golf club and detects a swing motion of the golf club, and an imaging portion that captures an image of a part of interest corresponding to the golf club.

Described herein are apparatus, systems and methods for shadow assisted object recognition and tracking. The methods performed by the apparatus and system include identifying a blob within a video image, the video image having at least one object and at least one shadow of the at least one object, the at least one shadow of the at least one object cast by at least one light source. Identifying the blob includes identifying an object projection corresponding to the at least one object and a shadow projection corresponding to the at least one shadow. A location of an object portion of the at least one object is determined based on the shadow projection.

A computing system identifies broadcast video for a plurality of games in a first league. The broadcast video includes a plurality of video frames. The computing system generates tracking data for each game from the broadcast video of a corresponding game. The computing system enriches the tracking data. The enriching includes merging play-by-play data for the game with the tracking data of the corresponding game. The computing system generates padded tracking data based on the tracking data. The computing system projects player performance in a second league for each player based on the tracking data and the padded tracking data.

Systems and methods are presented for detecting physical contacts effectuated by actions performed by an entity participating in an event. An action, performed by the entity, is detected based on a sequence of pose data associated with the entity's performance in the event. A contact with another entity in the event is detected based on data associated with the detected action. The action and the contact detections are employed by neural-network based detectors.

Systems and methods are presented for generating statistics associated with a performance of a participant in an event, wherein pose data associated with the participant, performing in the event, are processed in real time. Pose data associated with the participant may comprise positional data of a skeletal representation of the participant. Actions performed by the participant may be determined based on a comparison of segments of the participant's pose data to motion patterns associated with actions of interests.

A vital data measuring method includes: acquiring image data of a subject to be measured, wherein the image data are captured by a camera; analyzing the motion of the subject on the basis of the image data of the subject; starting measurement on vital data of the subject using a predetermined range of the image data of the subject in response to the detection of a certain pose of the subject based on an analysis; and outputting measurement results of the vital data of the subject.