One or more custom actions are stored in memory. Each of the custom actions is associated with a pattern of physical movement and a threshold. Physical movement data captured by a user device of the user is received and mapped to an identified one of the custom actions. When the physical movement data matches the associated pattern of physical movement within the associated threshold, it is determined that the user is authorized to access the identified custom action.

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.

The present disclosure provides a system and method for accurately detecting exercises performed by a user through a combination of signals from a visual input device and from one or more sensors of a wearable device. For each workout type, an algorithm leverages multimodal inputs for automatic workout detection/identification. Using multiple sources of visual and gestural inputs to detect the same workout results in a higher confidence in the detection. Moreover, it allows for continued detection of the workout, including counting repetitions, even when one or more signals becomes unavailable, such as if the user moves out of a field of view of the visual input device.

An exercise form analysis and feedback system (EFAF) including at least one sensor, at least one local movement data receiver, an analysis and feedback processing unit (AFPU) and a feedback display. The EFAF system of the present invention obtains lift movement data through the one or more sensors as lift movements are performed. This lift movement data may, in turn, be transmitted to one or more local movement data receivers such that the AFPU may operate on the lift movement data to provide real-time or near real-time form/technique feedback to the user via a feedback display. The system of the presentation invention uses machine learning techniques to provide feedback on lift quality aspects based on data associated with previous lifts and external data as applicable.

Example implementations described herein involve a system for training and managing machine learning models in an industrial setting. Specifically, by leveraging the similarity across certain production areas, it is possible to group such areas together to train models efficiently that use human pose data to predict human activities or specific task(s) that the workers are engaged in. Example implementations remove previous methods of independent model construction for each production area and takes advantage of the commonality amongst different environments.

Systems and methods are described for generating for presentation to a user at least one modified segment corresponding to a physical exercise depicted during presentation of a media asset to a user. The media asset may comprise multiple segments and one or more exercises, where each respective exercise corresponds to one or more segments, and input may be received from one or more sensors during presentation of the media asset, where the input is related to the user. Based on the received input, a determination may be made that an alternate version of an exercise corresponding to at least one particular segment of the multiple segments should be provided instead of a version of the exercise scheduled to be provided. The at least one particular segment may be modified to correspond to the alternate version of the exercise, and the at least one modified particular segment may be generated for presentation.

This application provides techniques of generating a virtual character for an online streamer. The techniques comprises obtaining a human body image of a target online streamer captured by an image collection device, wherein the human body image of the target online streamer comprises at least a face and an upper body part of the target online streamer; separately performing face recognition and upper-body limb recognition on the human body image to obtain face features and limb features; determining parameters associated with a virtual character corresponding to the target online streamer based on the face features and the limb features; and generating the virtual character corresponding to the target online streamer based on the parameters, wherein the generated virtual character has a motion and an expression corresponding to that of the target online streamer.

A computer implemented method for facilitating training of body-eye coordination using a computing device having access to a camera is disclosed. The method includes receiving a training video of a player from the camera; superimposing a visual cue onto the training video; extracting a body posture flow of the player from the training video by performing a computer vision algorithm on one or more frames of the training video; determining whether the player has responded to the visual cue by analyzing the body posture flow of the player; and generating a feedback to the player in response to determining that the player has responded to the visual cue. Multi-player embodiments of the present invention are also disclosed.

A system and method for reading and interpreting a wide range of nonverbal communicative cues, to include facial expression, pose, gesture, posture, and voice intonation. The output of this system is a scale between zero and one - with the scale indicating the interpretation of the nonverbal communication and accompanying text describing the interpretation. The system determines how a person intends to react and determines whether the person’s pronouncements are true or false.

Articles of sports equipment, such as striking implements (e.g., sticks) and wearable articles (e.g., skates, helmets) for playing hockey or other activities, in which at least one of the characteristics (e.g., stiffness) of the articles of sports equipment is adaptable and can be altered during use of the sports equipment, such as by comprising an alterable component coupled to a controller, by comprising an alterable component that is autonomously alterable, and/or by an alterable component that can be altered in response to a command of a remote device.