Abstract: Techniques related to automatically segmenting video frames into per pixel fidelity object of interest and background regions are discussed. Such techniques include applying tessellation to a video frame to generate feature frames corresponding to the video frame and applying a segmentation network implementing context aware skip connections to an input volume including the feature frames and a context feature volume corresponding to the video frame to generate a segmentation for the video frame.

Abstract: Techniques related to automatically segmenting a video frame into fine grain object of interest and background regions using a ground truth segmentation of an object in a previous frame are discussed. Such techniques apply multiple levels of segmentation tracking and prediction based on color, shape, and motion of the segmentation to determine per-pixel object probabilities, and solve an energy summation model to generate a final segmentation for the video frame using the object probabilities.

Abstract: An apparatus, method, system and computer readable medium for video tracking. An exemplar crop is selected to be tracked in an initial frame of a video. Bayesian optimization is applied with each subsequent frame of the video by building a surrogate model of an objective function using Gaussian Process Regression (GPR) based on similarity scores of candidate crops collected from a search space in a current frame of the video. A next candidate crop in the search space is determined using an acquisition function. The next candidate crop is compared to the exemplar crop using a Siamese neural network. Comparisons of new candidate crops to the exemplar crop are made using the Siamese neural network until the exemplar crop has been found in the current frame. The new candidate crops are selected based on an updated surrogate model.

Abstract: Techniques related to automatically segmenting video frames into per pixel dense object of interest and background regions are discussed. Such techniques include applying a segmentation convolutional neural network (CNN) to a CNN input including a current video frame, a previous video frame, an object of interest indicator frame, a motion frame, and multiple feature frames each including features compressed from feature layers of an object classification convolutional neural network as applied to the current video frame to generate candidate segmentations and selecting one of the candidate segmentations as a final segmentation of the current video frame.

Abstract: Systems and methods configured to process motion data associated with a user. The systems and methods are configured to receive motion data from a sensor, calculate motion attributes from the data, and classify the motion data using one or more mathematical models. Further, the systems and methods are configured to identify and quantify, using the one or more mathematical models, the motion data as linear travel motion associated with the user running or walking.

Abstract: A wrist-worn athletic performance monitoring system, including an analysis processor, configured to execute an activity recognition processes to recognize a sport or activity being performed by an athlete, and a sampling rate processor, configured to determine a sampling rate at which an analysis processor is to sample data from an accelerometer. The sampling rate processor may determine the sampling rate such that the analysis processor uses a low amount of electrical energy while still being able to carry out an activity classification process to classify an activity being performed.

Abstract: Analysis of sporting equipment characteristics may be analyzed using dynamic sampling rates. For example, analyzing a golf swing may include the use of one or more sensors providing data at various sampling rates. According to some aspects, the sampling rate may be dynamically modified upon determination of one or more golf equipment characteristics, environmental conditions, player characteristics and the like. In one example, a sampling rate processor may dynamically select a sampling rate at which data is sampled from one or more sensors. In some examples, by dynamically selecting the sampling rate, an analysis may be tailored to various types, and portions of a golf swing, in addition to producing power consumption by the analysis instruments in the golf club system. According to other aspects, triggering conditions for modifying a sampling rate may be determined from a population of one or more previous golf swings performed by a user.

Abstract: Processing techniques and device configurations for performing and controlling output effects at a plurality of wearable devices are generally described herein. In an example, a processing technique may include receiving, at a computing device, an indication of a triggering gesture that occurs at a first wearable device, determining an output effect corresponding to the indication of the triggering gesture, and in response to determining the output effect, transmitting commands to computing devices that are respectively associated with a plurality of wearable devices, the commands causing the plurality of wearable devices to generate the output effect at the plurality of wearable devices. In further examples, output effects such as haptic feedback, light output, or sound output, may be performed by the plurality of wearable devices, associated computing devices, or other controllable equipment.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed for generating an audiovisual response for an avatar. An example method includes converting a first digital signal representative of first audio including a first tone, the first digital signal incompatible with a model, to a plurality of binary values representative of a first characteristic value of the first tone, the plurality of binary values compatible with the model, selecting one of a plurality of characteristic values associated with a plurality of probability values output from the model, the probability values incompatible for output via a second digital signal representative of second audio, as a second characteristic value associated with a second tone to be included in the second audio, the second characteristic value compatible for output via the second digital signal, and controlling the avatar to output an audiovisual response based on the second digital signal and a first response type.

Abstract: Systems and methods may be used to provide effects corresponding to movement of instrument objects or other objects. A method may include receiving sensor data from an object based on movement of the object, recognizing a gesture from the sensor data, and determining an effect, such as a visualization or audio effect corresponding to the gesture. The method may include causing the effect to be output in response to the determination.

Abstract: Systems and methods may be used to provide effects corresponding to movement of instrument objects or other objects. A method may include receiving sensor data from an object based on movement of the object, recognizing a gesture from the sensor data, and determining an effect, such as a visualization or audio effect corresponding to the gesture. The method may include causing the effect to be output in response to the determination.

Abstract: Analysis of sporting equipment characteristics may be analyzed using dynamic sampling rates. For example, analyzing a golf swing may include the use of one or more sensors providing data at various sampling rates. According to some aspects, the sampling rate may be dynamically modified upon determination of one or more golf equipment characteristics, environmental conditions, player characteristics and the like. In one example, a sampling rate processor may dynamically select a sampling rate at which data is sampled from one or more sensors. In some examples, by dynamically selecting the sampling rate, an analysis may be tailored to various types, and portions of a golf swing, in addition to producing power consumption by the analysis instruments in the golf club system. According to other aspects, triggering conditions for modifying a sampling rate may be determined from a population of one or more previous golf swings performed by a user.

Abstract: Processing techniques and device configurations for performing and controlling output effects at a plurality of wearable devices are generally described herein. In an example, a processing technique may include receiving, at a computing device, an indication of a triggering gesture that occurs at a first wearable device, determining an output effect corresponding to the indication of the triggering gesture, and in response to determining the output effect, transmitting commands to computing devices that are respectively associated with a plurality of wearable devices, the commands causing the plurality of wearable devices to generate the output effect at the plurality of wearable devices. In further examples, output effects such as haptic feedback, light output, or sound output, may be performed by the plurality of wearable devices, associated computing devices, or other controllable equipment.

Abstract: The present disclosure describes a number of embodiments related to devices, systems, and methods locating a an object using ultra-wide band (UWB) radio transceivers embedded in carpet or other flexible material that may be rolled up and moved to various locations. Once in a location, the carpet may be unrolled and the multiple embedded radio transceivers may receive a signal from a tag attached to the object sending UWB radio signals. Based on the signals received by the UWB radio transceivers, various processes including time-difference on arrival, time-of-flight, and phase shift may be used to determine the location or the movement of the object.

Abstract: Analysis of sporting equipment characteristics may be analyzed using dynamic sampling rates. For example, analyzing a golf swing may include the use of one or more sensors providing data at various sampling rates. According to some aspects, the sampling rate may be dynamically modified upon determination of one or more golf equipment characteristics, environmental conditions, player characteristics and the like. In one example, a sampling rate processor may dynamically select a sampling rate at which data is sampled from one or more sensors. In some examples, by dynamically selecting the sampling rate, an analysis may be tailored to various types, and portions of a golf swing, in addition to producing power consumption by the analysis instruments in the golf club system. According to other aspects, triggering conditions for modifying a sampling rate may be determined from a population of one or more previous golf swings performed by a user.

Abstract: Gesture-controlled virtual reality systems and methods of controlling the same are disclosed herein. An example apparatus includes at least two of an on-body sensor, an off-body sensor, and an RF local triangulation system to detect at least one of a position or a movement of a body part of a user relative to a virtual instrument. The example apparatus includes a processor to generate an audio output of the virtual instrument in response to the at least one of the position or the movement.

Abstract: Processing techniques and device configurations for performing and controlling output effects at a plurality of wearable devices are generally described herein. In an example, a processing technique may include receiving, at a computing device, an indication of a triggering gesture that occurs at a first wearable device, determining an output effect corresponding to the indication of the triggering gesture, and in response to determining the output effect, transmitting commands to computing devices that are respectively associated with a plurality of wearable devices, the commands causing the plurality of wearable devices to generate the output effect at the plurality of wearable devices. In further examples, output effects such as haptic feedback, light output, or sound output, may be performed by the plurality of wearable devices, associated computing devices, or other controllable equipment.

Abstract: The present disclosure describes a number of embodiments related to devices, systems, and methods locating a an object using ultra-wide band (UWB) radio transceivers embedded in carpet or other flexible material that may be rolled up and moved to various locations. Once in a location, the carpet may be unrolled and the multiple embedded radio transceivers may receive a signal from a tag attached to the object sending UWB radio signals. Based on the signals received by the UWB radio transceivers, various processes including time-difference on arrival, time-of-flight, and phase shift may be used to determine the location or the movement of the object.

Abstract: Processing techniques and device configurations for performing and controlling output effects at a plurality of wearable devices are generally described herein. In an example, a processing technique may include receiving, at a computing device, an indication of a triggering gesture that occurs at a first wearable device, determining an output effect corresponding to the indication of the triggering gesture, and in response to determining the output effect, transmitting commands to computing devices that are respectively associated with a plurality of wearable devices, the commands causing the plurality of wearable devices to generate the output effect at the plurality of wearable devices. In further examples, output effects such as haptic feedback, light output, or sound output, may be performed by the plurality of wearable devices, associated computing devices, or other controllable equipment.

Abstract: A mechanism is described for facilitating smart placement of devices for implicit triggering of feedbacks relating to users' physical activities according to one embodiment. A method of embodiments, as described herein, includes detecting scanning, in real-time, of a body of a user during one or more physical activities being by the user, where scanning is performed by one or more sensors placed in one or more items located within proximity of the user. The method may further include receiving data from the one or more sensors, where the data includes biometric data relating to the user. The method may further include forming a feedback based on processing of the biometric data, and communicating, in real-time, the feedback using an object or one or more feedback devices.