Abstract:
Systems and methods share context information on a neighbor aware network. A method for communicating data in a wireless communications network is disclosed. The method includes receiving, by a device, a first message from a station, decoding the message to determine service information, the service information identifying a service provided by the station, generating a second message, wherein the second message is generated to indicate the service provided by the station and service information of the device, and transmitting, by the device, the second message to a remote station.
Abstract:
Exemplary methods, apparatuses, and systems infer a context of a user or device. A computer vision parameter is configured according to the inferred context. Performing a computer vision task, in accordance with the configured computer vision parameter. The computer vision task may by at least one of: a visual mapping of an environment of the device, a visual localization of the device or an object within the environment of the device, or a visual tracking of the device within the environment of the device.
Abstract:
Systems and methods for speech detection in association with a mobile device are described herein. A method described herein for identifying presence of speech associated with a mobile device includes obtaining a plurality of audio samples from the mobile device while the mobile device operates in a mode distinct from a voice call operating mode, generating spectrogram data from the plurality of audio samples, and determining whether the plurality of audio samples include information indicative of speech by classifying the spectrogram data.
Abstract:
A method of operating a shared resource in a mobile device includes extracting a set of features from a plurality of subsystems of the mobile device. The set of features may be extracted from each subsystem of the plurality of subsystems requesting services from one or more shared resources of the mobile device. One or more parameter of the shared resource(s) may be determined based on the extracted set of features from the plurality of subsystems. The shared resource(s) may be operated based on the determined parameter(s).
Abstract:
Methods, systems, computer-readable media, and apparatuses for determining indoor/outdoor state of a mobile device are presented. In some embodiments, a sensor reading is obtained from a sensor accessible by the mobile device. Contemporaneous information related to a local condition associated with an area where the mobile device is located is obtained. The sensor reading is provided as input to an indoor/outdoor detection model selected from a plurality of trained models, selected on the basis of the information related to the local condition. Based on the output of the model, the mobile device is classified as indoors or outdoors.
Abstract:
A method of controlling power consumption of a voice activation system in a mobile platform includes monitoring one or more sensors of the mobile platform. Next, it is determined whether a microphone of the mobile platform is concealed or obstructed in response to the monitoring of the one or more sensors. If so, the mobile platform transitions one or more components of the voice activation system from a normal power consumption power state to a low power consumption state.
Abstract:
Disclosed is an apparatus and method for classifying a motion state of a mobile device comprising: determining a first motion state associated with a highest probability value and with a first confidence level greater than a first threshold; entering the first motion state; while the first motion state is active, determining a second motion state associated with a highest probability value and with a second confidence level greater than the first threshold, the second motion state being different from the first motion state; determining whether the second motion state is to be entered; and in response to determining that the second motion state is to be entered, entering the second motion state.
Abstract:
Systems, apparatus and methods in a mobile device to enable and disable a depth sensor for tracking pose of the mobile device are presented. A mobile device relaying on a camera without a depth sensor may provide inadequate pose estimates, for example, in low light situations. A mobile device with a depth sensor uses substantial power when the depth sensor is enabled. Embodiments described herein enable a depth sensor only when images are expected to be inadequate, for example, accelerating or moving too fast, when inertial sensor measurements are too noisy, light levels are too low or high, an image is too blurry, or a rate of images is too slow. By only using a depth sensor when images are expected to be inadequate, battery power in the mobile device may be conserved and pose estimations may still be maintained.
Abstract:
Disclosed is a system, apparatus, computer readable storage medium, and method to perform a context inference for a mobile device. In one embodiment, a data processing system includes a processor and a storage device configurable to store instructions to perform a context inference for the data processing system. Data may be received from at least a first sensor, and a first classification of the data from the sensor may be performed. Confidence for the first classification can be determined and a second sensor can be activated based on a determination that the confidence fails to meet a confidence threshold. A data sample classification from the activated second sensor may be classified jointly with the data from first sensor.
Abstract:
Methods, systems, computer-readable media, and apparatuses for inferring context are provided. In one potential implementation, first context information associated with a first duration is identified, second context information is accessed to determine a context segmentation boundary; and the first context information and the second context information is then aggregated to generate an inferred segmented aggregated context. In a further implementation, the first context information is used to average inferred contexts, and the context segmentation boundary is used to reset a start time for averaging the first context information.