Abstract:
Sensor data from a sensor system of a mobile device may be used for determining a level of pressure exerted by a user on the mobile device. The sensor system may include one or more types of sensors, such as a microphone and one or more inertial sensors. The inertial sensors may include one or more gyroscopes and/or accelerometers. Based on the inertial sensor data, it may be determined whether and/or how the mobile device is being held. A process for determining a level of pressure exerted by a user on the mobile device may be adapted based, at least in part, on whether and/or how the mobile device is being held. The pressure-determining process may be adapted according to various other criteria, such as a position of a touch target in a display, ambient noise levels, etc.
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:
System and methods for performing context inference in a computing device are disclosed. In one embodiment, a method of performing context inference includes: determining, at a computing device, a first context class using context-related data from at least one data source associated with a mobile device; and determining, at the mobile device, a fusion class based on the first context class, the fusion class being associated with at least one characteristic that is common to the first context class and a second context class that is different from the first context class.
Abstract:
Methods, systems, computer-readable media, and apparatuses for determining indoor/outdoor state of a mobile device are presented. In some embodiments, a mobile device may maintain an indoor/outdoor state. The mobile device may include at least one first sensor and at least one second sensor, the first sensor associated with higher power consumption than the second sensor. The mobile device may gate off the first sensor and using the second sensor to obtain a sensor reading, if the second sensor can generate a reading indicative of the indoor/outdoor state of the mobile device. The mobile device may use the first sensor to obtain a sensor reading, if the second sensor cannot generate a reading indicative of the indoor/outdoor state of the mobile device. The mobile device may update the indoor/outdoor state of the mobile device based on a reading received from one of the first and the second sensors.
Abstract:
Systems and methods for applying and using context labels for data clusters are provided herein. A method described herein for managing a context model associated with a mobile device includes obtaining first data points associated with a first data stream assigned to one or more first data sources; assigning ones of the first data points to respective clusters of a set of clusters such that each cluster is respectively assigned ones of the first data points that exhibit a threshold amount of similarity and are associated with times within a threshold amount of time of each other; compiling statistical features and inferences corresponding to the first data stream or one or more other data streams assigned to respective other data sources; assigning context labels to each of the set of clusters based on the statistical features and inferences.
Abstract:
System and methods are disclosed to use information available on the state of mobile devices in a heuristics-based approach to improve motion state detection. In one or more embodiments, information on the WiFi connectivity of mobile devices may be used to improve the detection of the in-transit state. The WiFi connectivity information may be used with sensor signal such as accelerometer signals in a motion classifier to reduce the false positives of the in-transit state. In one or more embodiments, information that a mobile device is connected to a WiFi access point (AP) may be used as heuristics to reduce the probability of falsely classifying the mobile device in the in-transit state when mobile device is actually in the hand of a relatively stationary user. Information on the battery charging state or the wireless connectivity of the mobile devices may also be used to improve the detection of in-transit state.
Abstract:
Sensor data from a sensor system of a mobile device may be used for determining a level of pressure exerted by a user on the mobile device. The sensor system may include one or more types of sensors, such as a microphone and one or more inertial sensors. The inertial sensors may include one or more gyroscopes and/or accelerometers. Based on the inertial sensor data, it may be determined whether and/or how the mobile device is being held. A process for determining a level of pressure exerted by a user on the mobile device may be adapted based, at least in part, on whether and/or how the mobile device is being held. The pressure-determining process may be adapted according to various other criteria, such as a position of a touch target in a display, ambient noise levels, etc.
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 transition triggered context monitoring for a mobile device. A first sensor data stream comprising data from one or more sensors at the mobile device is received. One or more features calculated from the data of the first sensor data stream may be monitored and a status change for the one or more features is detected. In response to detecting the status change, of a second sensor data stream comprising data from one or more sensors at the mobile device is collected. The second sensor data stream may be processed as a context label for a segment of the first sensor data stream and the segment beginning may be defined by the status change.
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.