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: Methods and systems for detecting a player in a gaming environment using a mobile device are disclosed. The methods and systems perform the steps of receiving calibration data from a camera of a user device, the calibration data comprising a first reference point associated with the gaming environment, a second reference point associated with the gaming environment, and sensor data associated with the user device; computing a camera projection based on the first reference point, the second reference point, and the sensor data obtained from the user device; receiving an input video of the gaming environment, wherein the input video is captured using the camera, and wherein frames of the input video comprise at least one player in the gaming environment; identifying an image location of the player by performing a computer vision algorithm on the input video; and determining a real-world location of the player based on the image location and the camera projection.

Abstract: Methods and systems are disclosed for real-time tracking of a multiplayer ball game using a mobile computing device. The methods and systems are configured to receive an input video of the multiplayer ball game captured using a camera on the mobile computing device in a gaming area associated with n players, where n is an integer and n?2; detect a plurality of player postures, by performing a computer vision algorithm on each of a plurality of frames of the input video; extract an associated player feature from each of the plurality of player postures; assign each of the plurality of player postures, based on the associated player feature, to one of at least n posture groups, where each player is represented by one of the at least n posture groups; and determine a player location for each player, based on the player's posture group.

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 virtual coaching and performance training using a mobile device are disclosed. The methods and systems perform the steps of capturing a training video of one or more players, using the camera on the mobile computing device; superimposing a visual cue onto the training video at a first location and for a cue period starting from a first time instant; determining whether at least one of the one or more players has responded to the visual cue at a second time instant within the cue period, by analyzing a body posture flow of each player between the first time instant and the second time instant, wherein each body posture flow is extracted from the training video by performing a computer vision algorithm on one or more frames of the training video; and in response to determining that at least one player has responded to the visual cue, generating a feedback to the one or more players.

Abstract: Methods and systems for detecting a player in a gaming environment using a mobile device are disclosed. The methods and systems perform the steps of receiving calibration data from a camera of a user device, the calibration data comprising a first reference point associated with the gaming environment, a second reference point associated with the gaming environment, and sensor data associated with the user device; computing a camera projection based on the first reference point, the second reference point, and the sensor data obtained from the user device; receiving an input video of the gaming environment, wherein the input video is captured using the camera, and wherein frames of the input video comprise at least one player in the gaming environment; identifying an image location of the player by performing a computer vision algorithm on the input video; and determining a real-world location of the player based on the image location and the camera projection.

Abstract: Methods and systems for remote real-time or asynchronous multiplayer gameplay using mobile devices are disclosed. The methods and systems include steps of mounting mobile computing devices in gaming areas associated with users; initiating a game between the users; analyzing movements of the users, ball(s), and/or other game equipment of the game by performing a computer vision algorithm on one or more frames of an input video of the game; and providing feedback to the users, where feedback may include instructions to be performed by the users and player analytics. 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.

Abstract: Methods and systems for mobile device-based touchless control can include receiving an image of a user and applying a convolutional neural network to the image to determine a feature map. Further, a key-points map and an affinity-field map can be determined based on the feature map, and the pose of the user can be determined based on the maps. The methods and system further include identifying an activation gesture of the user and determining a validity of a bounding box associated with the pose of the user, and tracking the pose of the user and a portion of a body of the user for performing the touchless control. Further, the methods and systems include determining a mapping between the portion of the user's body and a cursor position associated with an application, and moving the cursor position to enable touchless user interaction. Embodiments use computer vision techniques to enable a resource-limited mobile device to conduct the aforementioned steps.

Abstract: Methods and systems for virtual coaching and performance training using a mobile device are disclosed. The methods and systems perform the steps of capturing a training video of a player using a camera on the mobile device; augmenting the training video with a visual cue for a cue period starting from a first time instant; determining whether the player has responded to the visual cue at a second time instant within the cue period, by analyzing a body posture flow of the player between the first time instant and the second time instant, wherein the body posture flow is extracted from the training video by performing a computer vision algorithm on one or more frames of the training video; and in response to determining that the player has responded to the visual cue, generating a feedback to the player.

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 are disclosed for real-time tracking of a multiplayer ball game using a mobile computing device. The methods and systems are configured to receive an input video of the multiplayer ball game captured using a camera on the mobile computing device in a gaming area associated with n players, where n is an integer and n?2; detect a plurality of player postures, by performing a computer vision algorithm on each of a plurality of frames of the input video; extract an associated player feature from each of the plurality of player postures; assign each of the plurality of player postures, based on the associated player feature, to one of at least n posture groups, where each player is represented by one of the at least n posture groups; and determine a player location for each player, based on the player's posture group.

Abstract: Methods and systems for remote real-time or asynchronous multiplayer gameplay using mobile devices are disclosed. The methods and systems include steps of mounting mobile computing devices in gaming areas associated with users; initiating a game between the users; analyzing movements of the users, ball(s), and/or other game equipment of the game by performing a computer vision algorithm on one or more frames of an input video of the game; and providing feedback to the users, where feedback may include instructions to be performed by the users and player analytics. 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.

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 ball shot attempt detection and game analytics generation are disclosed. The methods and systems perform steps to receive an input video of a ball gameplay, wherein the input video was captured using a stationary camera, and wherein frames of the input video comprises a goal; identify a Region of Interest (ROI) surrounding the goal by performing a first computer vision algorithm on the input video; detect a ball within the ROI during a shot attempt and determining a trajectory of the ball by performing a second computer vision algorithm on the input video; and identify a player relevant to the shot attempt based on the trajectory of the ball. In some embodiments, the computer vision algorithms comprise a convolution neural network (CNN). The present invention uses computer vision techniques to enable a resource-limited mobile device such as a smartphone to efficiently execute the new process.

Abstract: Methods and systems for ball shot attempt detection and game analytics generation are disclosed. The methods and systems perform steps to receive an input video of a ball gameplay, wherein the input video was captured using a stationary camera, and wherein frames of the input video comprises a goal; identify a Region of Interest (ROI) surrounding the goal by performing a first computer vision algorithm on the input video; detect a ball within the ROI during a shot attempt and determining a trajectory of the ball by performing a second computer vision algorithm on the input video; and identify a player relevant to the shot attempt based on the trajectory of the ball. In some embodiments, the computer vision algorithms comprise a convolution neural network (CNN). The present invention uses computer vision techniques to enable a resource-limited mobile device such as a smartphone to efficiently execute the new process.

Abstract: Visual comparison of document versions is described. In some implementations, versions of a document can be quickly displayed using a single user input. In some implementations, a displayed page of a version of the document can be replaced by a corresponding page of another version of the document.

Abstract: A disc drive includes a base and a disc rotatably attached to the base. The disc drive is formatted by obtaining a list of defective sector entries, determining a first location of selected information based on skipping the defective sectors within the list of defective sector entries, and calculating a second location for selected information. At least one sector to skip is added before the second location of selected information to move the selected information from the first position to the second position. The added sectors may be designated as defective sectors. By adding the at least one sector to skip, the second position of the information is moved or slipped.

Abstract: A system for adapting head switching sequence in a disc drive includes a method of measuring the time duration for a head switch operation and the time duration of a track switch operation. The system compares the two time durations to determine whether head switching or track switching should be utilized within a zone of tracks on the surface of the data disc. Track switch time durations and head switch time durations may be averaged within a zone and the averages compared to determine whether to use head switching or track switching.

Abstract: According to one embodiment of the present invention a disc controller in a disc drive includes a cache memory and a control circuit. The control circuit is configured to identify an operating system of a host computer coupled to the disc drive, select a segmentation level for the cache memory based on the identified operating system, and store information in the cache memory according to the segmentation level. According to another embodiment of the present invention a cache memory in a disc drive is operated by identifying an operating system of a host computer coupled to the disc drive, selecting a segmentation level for the cache memory based on the identified operating system, and storing information in the cache memory according to the segmentation level. The operating system is identified by reading a partition type from a master boot record stored in a disc in the disc drive.

Abstract: The present invention pertains to an apparatus and method for recording data in a variable bit density disc drive. The disc drive includes a recording surfaces, each having a corresponding head for recording data on the recording surface. At least one head is operated at a different recording frequency from the other heads, creating a variable bit density for the different recording surfaces. The combination of head recording frequencies is determined following an error testing operation and a unique physdisc lookup table is created based on the determined recording frequencies. The physdisc lookup table is used to allocate data sectors and to convert between logical and physical block addresses.