Abstract:
Implementations of the disclosed subject matter provide techniques for improved identification of a gesture based on data obtained from multiple devices. A method may include receiving an indication of an onset of a gesture, from a first device, at a gesture coordinating device. Next, first subsequent data describing the gesture may be received from a second device, at the gesture coordinating device. Based on the indication and the first subsequent data, the gesture may be identified. In response to identification of the gesture, an action may be performed based on the gesture identified. In some cases, the gesture coordinating device may be a cloud-based device.
Abstract:
Implementations of the disclosed subject matter provide techniques for improved identification of a gesture based on data obtained from multiple devices. A method may include receiving an indication of an onset of a gesture, from a first device, at a gesture coordinating device. Next, first subsequent data describing the gesture may be received from a second device, at the gesture coordinating device. Based on the indication and the first subsequent data, the gesture may be identified. In response to identification of the gesture, an action may be performed based on the gesture identified. In some cases, the gesture coordinating device may be a cloud-based device.
Abstract:
Implementations of the disclosed subject matter provide techniques for improved identification of a gesture based on data obtained from multiple devices. A method may include receiving an indication of an onset of a gesture, from a first device, at a gesture coordinating device. Next, first subsequent data describing the gesture may be received from a second device, at the gesture coordinating device. Based on the indication and the first subsequent data, the gesture may be identified. In response to identification of the gesture, an action may be performed based on the gesture identified. In some cases, the gesture coordinating device may be a cloud-based device.
Abstract:
The present disclosure provides techniques for improving IMU-based gesture detection by a device using ultrasonic Doppler. A method may include detecting the onset of a gesture at a first device based on motion data obtained from an IMU of the first device. An indication of the detection of the onset of the gesture may be provided to a second device. Next, a first audio signal may be received from the second device. As a result, the gesture may be identified based on the motion data and the received first audio signal. In some cases, a first token encoded within the first audio signal may be decoded and the first token may be provided to a third coordinating device. A confirmation message may be received from the third coordinating device based on the first token provided and identifying the gesture may be further based on the confirmation message.
Abstract:
The present disclosure provides techniques for improving IMU-based gesture detection by a device using ultrasonic Doppler. A method may include detecting the onset of a gesture at a first device based on motion data obtained from an IMU of the first device. An indication of the detection of the onset of the gesture may be provided to a second device. Next, a first audio signal may be received from the second device. As a result, the gesture may be identified based on the motion data and the received first audio signal. In some cases, a first token encoded within the first audio signal may be decoded and the first token may be provided to a third coordinating device. A confirmation message may be received from the third coordinating device based on the first token provided and identifying the gesture may be further based on the confirmation message.
Abstract:
A system and method that includes detecting an application change within a multi-application operating framework; updating an application hierarchy model for gesture-to-action responses with the detected application change; detecting a gesture; according to the hierarchy model, mapping the detected gesture to an action of an application; and triggering the action.
Abstract:
System and method for image detection that include collecting image data; at a processor, over a plurality of support regions of the image data, computing a dimensionality component of a support region of the image data, wherein the, non-nucleus pixels of a support region; calculating a normalizing factor of the dimensionality component; for at least one weighted pattern of a pattern set, applying a weighted pattern to the dimensionality component to create a gradient vector, mapping the gradient vector to a probabilistic model, and normalizing the gradient vector by the normalizing factor; condensing probabilistic models of the plurality of support regions into a probabilistic distribution feature for at least one cell of the image data; applying a classifier to at least the probabilistic distribution feature; and detecting an object in the image data according to a result of the applied classifier.