Abstract: Methods and systems for remote multiplayer gameplay are disclosed. An example method can include joining a multiplayer interactive physical game including first and second players competing in an activity; capturing a first game video of a first player in a first play of the multiplayer interactive physical game, using a first camera on a first mobile computing device in a first gaming area; determining a first object flow associated with the first player from the first game video, by performing an algorithm on one or more frames of the first game video to detect one or more key points of the first player; generating a first analytic based on the first object flow; receiving a second analytic associated with the second player in a second gaming area; and generating a feedback to the first player based on the first analytic or the second analytic.

Abstract: Systems and methods for motion tracking on a hardware device without a camera and/or without a sufficiently powerful hardware processor, by offloading pose processing fully or partially to a mobile device, are disclosed. Methods executable on the hardware device include receiving pose data associated with a user from the mobile device, and performing a touchless control of an application on the hardware device, based on the received pose data. Methods executable on the mobile device include capturing at least one image associated with a user, performing a pose recognition algorithm on the mobile device, based on the captured image, to generate pose data for performing a touchless control of an application on the hardware device, and transmitting the pose data to the hardware device, using the network connection. The methods and systems include embodiments where the pose recognition algorithm uses machine learning.

Abstract: 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.

Abstract: Methods and systems for performing location and movement determination in a three-dimensional environment using a device with a camera are disclosed. The methods and systems perform the steps of capturing an image of a user using the camera of the computing device, identifying the user from the image using a first algorithm, determining a first physical information associated with the user using a first algorithm, determining a second physical information of the user based on the first physical information and an input parameter of the user using a search process, and determining the location of the user in the environment based on the first physical information and the second physical information.

Abstract: Methods and systems for touchless control of a device include receiving an image from a camera and applying a machine learning technique the image to determine a first map, the first map including a function that generates a correspondence between data associated with the image to a feature space. A second map including a representation of a user in the image can be determined based on the first map. Further, a pose of the user can be determined based on the second map. The pose of the user and a portion of a body of the user can be tracked to determine a mapping between the portion of the user's body and an input feature of a device. The input feature can be modified based on the mapping to enable a touchless interaction between the user and the device.

Abstract: A system and method for implementing a virtual fitness application are disclosed. Embodiments may be built for various platforms, including web browsers and mobile phones. One embodiment uses pose estimation to count the repetitive motions of a fitness activity (e.g., running). In one embodiment, to count the repetitive motions, a repetitive motion counting process is used that is based on computing differences of Y-coordinates of key points of the user. The repetitive motion counting process includes selecting a proper pose of the user; computing one or more delta values (corresponding to Y-coordinate changes of the key points); and counting a given user movement as a repetitive motion based on a function (e.g., average) of the delta values. One embodiment uses the pose estimation and repetitive motion count results to provide a gamified experience, for example, a leaderboard, a stats report, instant visual feedback, badges, coins, and a social experience.

Abstract: Methods and systems for image clustering are described, and include first receiving a plurality of images from a video of a game. Next, determining a first feature vector of a first player from the plurality of images by inputting the plurality of images to an artificial intelligence (AI)-based process. Next, dividing the plurality of images into a first subset of images and a second subset of images based on the first feature vector. Next, receiving a first identifier tagging the first player in a first image of the first subset. Finally, identifying a second player in a second image in the second subset by propagating the first identifier of the first subset, based on a distance measure associated with the first feature vector from the artificial intelligence (AI)-based process. Running on a mobile computing device, the method allows multiplayer tagging to be easily performed in almost any environment.

Abstract: Methods and systems for multi-player training of body-eye coordination using mobile computing devices each having a camera are provided. The methods and systems execute instructions to capture a first training video of a first of player, using a first camera on a first mobile computing device; superimpose a visual cue onto the first training video at a visual cue location and for a cue period starting from a first time instant; determine whether the first player has responded to the visual cue at a second time instant within the cue period; receive a notification from a second mobile computing device, where the notification was generated in response to determining that a second player has responded to the visual cue at a third time instant within the cue period; and in response to a determination that the first player has responded to the visual cue and to the notification, generate a feedback to the first player.

Abstract: Methods and systems for real-time generation of ball shot analytics are disclosed. The methods and systems perform steps for ball and posture detection, ball and posture flow generation, shot event identification and classification, and shot analytics generation based on identified shot events and shooter posture flow. Embodiments of the present invention use computer vision techniques to enable a resource-limited mobile device such as a smartphone to conduct the aforementioned steps. Also disclosed are benefits of the new methods, and alternative embodiments of implementation.

Abstract: 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.

Abstract: Methods and systems for constructing a three-dimensional (3D) model of a user in a virtual environment for full body virtual reality (VR) applications are described. The method includes receiving an image of the user captured using an RGB camera; detecting a body bounding box associated with the user using a first trained neural network; determining a segmentation map of the user, based on the body bounding box; determining a two-dimensional (2D) contour of the user from the segmentation map; forming a 3D extrusion model by extruding the 2D contour; and constructing the 3D model of the user in the virtual environment by applying a geometric transformation to the 3D extrusion model. Applications of full body VR include physical training and fitness sessions, games, control of computing devices, manipulation and display of data, interactive social media with VR, and the like.

Abstract: Methods and systems for determining and classifying a number of repetitive motions in a video are described, and include the steps of first determining a plurality of images from a video, where the images are segmented from at least one video frame of the video. Next, performing a pose detection process on a feature of the images to generate one or more landmarks. Next, determining one or more principle component axes on points associated with a given landmark. Finally, determining at least one repetitive motion based on a pattern associated with a projection of the points onto the one or more principle components. In some embodiments, the disclosed methods can classify the repetitive motions to respective types. The present invention can be implemented for convenient use on a mobile computing device, such as a smartphone, for tracking exercises and similar repetitive motions.

Abstract: Methods and systems for determining a ball shot attempt result, the ball shot attempt captured by a camera on a mobile computing device, are disclosed. The methods and systems perform steps comprising receiving an input video captured using the camera on the mobile computing device, wherein the input video comprises a ball shot attempt at a goal; receiving a declared ball shot attempt, the declared ball shot attempt detected by analyzing a ball trajectory in the input video; detecting an element movement associated with an element of the goal; and determining the ball shot attempt result based on the element movement and the ball trajectory. In some embodiments, the element of the goal is a net, and the declared ball shot attempt is detected by analyzing the ball trajectory in a ball shot attempt Region of Interest (ROI) within frames of the input video.

Abstract: Methods and systems for remote multiplayer gameplay are disclosed. An example method can include joining a multiplayer interactive physical game including first and second players competing in an activity; capturing a first game video of a first player in a first play of the multiplayer interactive physical game, using a first camera on a first mobile computing device in a first gaming area; determining a first object flow associated with the first player from the first game video, by performing an algorithm on one or more frames of the first game video to detect one or more key points of the first player; generating a first analytic based on the first object flow; receiving a second analytic associated with the second player in a second gaming area; and generating a feedback to the first player based on the first analytic or the second analytic.

Abstract: Methods and systems for image clustering are described, and include determining a plurality of images from a video of a game, the video captured by a camera on a mobile device, where at least one image of the plurality of images is segmented from a video frame of the video; determining a feature vector from the at least one image; dividing the images into a first subset and a second subset based on the feature vector; tagging a first player in a first image of the first subset with an identifier, where the identifier differentiates the images in the first subset to a plurality of players; and identifying a second player in a second image in the second subset by propagating the identifier of the first subset, based on a distance measure associated with the feature vector. Running on a mobile computing device, this invention allows multiplayer tagging to be easily performed in almost any environment.

Abstract: Methods and systems for 3D ball trajectory reconstruction are disclosed. The methods and systems perform steps of receiving a 2D ball trajectory, a shooter's on-ground foot location, and a camera projection matrix; generating on-ground trajectory line assumptions based on the shooter's on-ground foot location and the 2D trajectory; reconstructing a candidate 3D trajectory for each on-ground trajectory line assumption, by determining a ball height for each on-ground projection point in the on-ground trajectory line and by curve fitting; evaluating each candidate 3D trajectory and selecting one with a best score as the reconstructed 3D ball trajectory. Embodiments of the present invention enable a resource-limited mobile device such as a smartphone to conduct the aforementioned steps. Also disclosed are benefits of the new methods, and alternative embodiments of implementation.

Abstract: Methods and systems for performing location and movement determination in a three-dimensional environment using a mobile device with a camera are disclosed. The methods and systems perform the steps of capturing one or more images of a user using the camera on the mobile computing device, determining the user from the images using a machine learning algorithm, determining a pose associated with the user using a machine vision algorithm, determining a depth of the user with respect to the camera based on the pose and an input height of the user using a binary search process, and determining the location of the user in the environment based on the pose and the depth.