Abstract:
Disclosed are systems, apparatus, devices, method, computer program products, and other implementations, including a method that includes capturing an image of a scene by an image capturing unit of a device that includes at least one sensor, determining relative device orientation of the device based, at least in part, on determined location of at least one vanishing point in the captured image of the scene, and performing one or more calibration operations for the at least one sensor based, at least in part, on the determined relative device orientation.
Abstract:
In one implementation, a method may comprise: storing a user profile indicative of at least one attribute of a user of a mobile station; determining a measurement value based, at least in part, on a signal from at least one sensor on the mobile station; and estimating a location of the mobile station based, at least in part, on an association of the at least one attribute and the measurement value with a context parameter map database.
Abstract:
Various techniques are provided for identifying a position uncertainty of a mobile device, such as, based, at least in part, on a measure of potential hindrance of an estimated trajectory. For example, an example method may comprise estimating a trajectory of the mobile device within a particular environment, determining a measure of potential hindrance for at least a portion of the trajectory based, at least in part, on an electronic map that is indicative of a presence or an absence of one or more obstacles, and presenting an indication of a position uncertainty to a user of the mobile device. The position uncertainty may be based, at least in part, on the measure of potential hindrance.
Abstract:
Disclosed are systems, apparatus, devices, method, computer program products, and other implementations, including a method that includes capturing an image of a scene by an image capturing unit of a device that includes at least one sensor, determining relative device orientation of the device based, at least in part, on determined location of at least one vanishing point in the captured image of the scene, and performing one or more calibration operations for the at least one sensor based, at least in part, on the determined relative device orientation.
Abstract:
Techniques are provided for adaptively sampling orientation sensors in positioning systems based on location (e.g., map) data. Embodiments can enable a device to use location, direction, and/or location information to anticipate an expected change in motion. The embodiments can then identify and prioritize a number of sampling strategies to alter sampling rates of orientation sensors, and implement at least one strategy, based on priority.
Abstract:
Performance of step detectors in mobile devices can be enhanced by calculating the probability of a step and providing the probability to an application. Adaptive data models can also be used that can be based on different types of motion (walking with mobile device in hand, climbing stairs with mobile device in purse, running with mobile device in pocket, etc.), and can adapt to a particular user's motion. Where applications allow, embodiments can further utilize data modeling to detect a pattern (e.g., a series of steps) and adjust the probability calculation accordingly.
Abstract:
Disclosed is a method for position determination, including altering or generating at least one radio heatmap value in a collection of radio heatmap values, the altering or generating based, at least in part, on a measurement of one or more characteristics of wireless signals received by a receiver at a first wireless network access point and transmitted by a transmitter at a second wireless network access point; and transmitting at least a portion of the collection of radio heatmap values including the altered or generated radio heatmap value to a mobile station as positioning assistance information.
Abstract:
Techniques for position estimation, e.g., of a mobile communication device, using trajectory are described herein. A method for estimating position of a mobile device described herein includes obtaining a routing graph corresponding to an area, wherein the routing graph indicates traversable paths through the area; collecting trajectory information corresponding to movement of the mobile device through the area; forming a trajectory graph from the trajectory information; comparing the trajectory graph to at least one subset of the routing graph to determine at least one matching subset of the routing graph; and estimating the position of the mobile device based at least in part on the at least one matching subset of the routing graph.
Abstract:
Methods and apparatuses for modeling characteristics of a venue are disclosed. The method comprises identifying a set of constraints associated with the venue, determining a plurality of paths to be traveled by one or more mobile devices in accordance with the set of constraints, directing the one or more mobile devices to navigate the venue using the plurality of paths, receiving data collected by the one or more mobile devices, and generating a model of the venue using the data collected by the one or more mobile devices.
Abstract:
In one implementation, a method may comprise: storing a user profile indicative of at least one attribute of a user of a mobile station; determining a measurement value based, at least in part, on a signal from at least one sensor on the mobile station; and estimating a location of the mobile station based, at least in part, on an association of the at least one attribute and the measurement value with a context parameter map database.